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TSD_test_item_200
WTQ_202-csv_258.jpg
Provide me with the row number and column number for the table shown in this image. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> | 1980 | 1975 | 1975 | 1985 | 1985 World | 4,434,682,000 | 4,068,109,000 | 366,573,000 | 4,830,979,000 | 396,297,000 Africa | 469,618,000 | 408,160,000 | 61,458,000 | 541,814,000 | 72,196,000 Asia | 2,632,335,000 | 2,397,512,000 | 234,823,000 | 2,887,552,000 | 255,217,000 Europe | 692,431,000 | 675,542,000 | 16,889,000 | 706,009,000 | 13,578,000 Latin-America & Caribbean | 361,401,000 | 321,906,000 | 39,495,000 | 401,469,000 | 40,068,000 North America | 256,068,000 | 243,425,000 | 12,643,000 | 269,456,000 | 13,388,000 Oceania | 22,828,000 | 21,564,000 | 1,264,000 | 24,678,000 | 1,850,000
WTQ_for_TSD
| 1980 | 1975 | 1975 | 1985 | 1985 World | 4,434,682,000 | 4,068,109,000 | 366,573,000 | 4,830,979,000 | 396,297,000 Africa | 469,618,000 | 408,160,000 | 61,458,000 | 541,814,000 | 72,196,000 Asia | 2,632,335,000 | 2,397,512,000 | 234,823,000 | 2,887,552,000 | 255,217,000 Europe | 692,431,000 | 675,542,000 | 16,889,000 | 706,009,000 | 13,578,000 Latin-America & Caribbean | 361,401,000 | 321,906,000 | 39,495,000 | 401,469,000 | 40,068,000 North America | 256,068,000 | 243,425,000 | 12,643,000 | 269,456,000 | 13,388,000 Oceania | 22,828,000 | 21,564,000 | 1,264,000 | 24,678,000 | 1,850,000
Provide me with the row number and column number for the table shown in this image. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_201
WTQ_204-csv_271.jpg
What is the count of rows and columns in the given table? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> Opus | Title | Sub­divisions | Compo-sition | Première date | Place, theatre 1 | Der Bärenhäuter | 3 acts | 1898 | 22 January 1899 | Munich, Hofopera 2 | Herzog Wildfang | 3 acts | 1900 | 23 March 1901 | Munich, Hofopera 3 | Der Kobold | 3 acts | 1903 | 29 January 1904 | Hamburg, Stadttheater 4 | Bruder Lustig | 3 acts | 1904 | 13 October 1905 | Hamburg, Stadttheater 5 | Sternengebot | prologue and 3 acts | 1906 | 21 January 1908 | Hamburg, Stadttheater 6 | Banadietrich | 3 acts | 1909 | 23 January 1910 | Karlsruhe, Hoftheater 7 | Schwarzschwanenreich | 3 acts | 1910 | 5 November 1918 | Karlsruhe, Hoftheater 8 | Sonnenflammen | 3 acts | 1912 | 30 October 1918 | Darmstadt, Hoftheater 9 | Der Heidenkönig | prologue and 3 acts | 1913 | 16 December 1933 | Cologne, Städtische Bühnen 10 | Der Friedensengel | 3 acts | 1914 | 4 March 1926 | Karlsruhe, Badisches Landestheater 11 | An allem ist Hütchen Schuld! | 3 acts | 1915 | 6 December 1917 | Stuttgart, Hofopera 12a | Das Liebesopfer (libretto only, no music completed) | 4 acts | 1917 | | 13 | Der Schmied von Marienburg | 3 acts | 1920 | 16 December 1920 | Rostock, Städtische Bühnen 14 | Rainulf und Adelasia | 3 acts | 1922 | 1923 | Rostock (prelude only) 15 | Die heilige Linde | 3 acts | 1927 | 2001 | Keulen (prelude only) 16 | Wahnopfer | 3 acts | 1928 | 1994 | Rudolstadt, Heidecksburg only libretto and Act 1 finished 17 | Walamund (libretto only, no music completed) | 3 acts | 1928 | | 18 | Das Flüchlein, das Jeder mitbekam | 3 acts | 1929 | 29 April 1984 | Kiel (completed by Hans Peter Mohr)
WTQ_for_TSD
Opus | Title | Sub­divisions | Compo-sition | Première date | Place, theatre 1 | Der Bärenhäuter | 3 acts | 1898 | 22 January 1899 | Munich, Hofopera 2 | Herzog Wildfang | 3 acts | 1900 | 23 March 1901 | Munich, Hofopera 3 | Der Kobold | 3 acts | 1903 | 29 January 1904 | Hamburg, Stadttheater 4 | Bruder Lustig | 3 acts | 1904 | 13 October 1905 | Hamburg, Stadttheater 5 | Sternengebot | prologue and 3 acts | 1906 | 21 January 1908 | Hamburg, Stadttheater 6 | Banadietrich | 3 acts | 1909 | 23 January 1910 | Karlsruhe, Hoftheater 7 | Schwarzschwanenreich | 3 acts | 1910 | 5 November 1918 | Karlsruhe, Hoftheater 8 | Sonnenflammen | 3 acts | 1912 | 30 October 1918 | Darmstadt, Hoftheater 9 | Der Heidenkönig | prologue and 3 acts | 1913 | 16 December 1933 | Cologne, Städtische Bühnen 10 | Der Friedensengel | 3 acts | 1914 | 4 March 1926 | Karlsruhe, Badisches Landestheater 11 | An allem ist Hütchen Schuld! | 3 acts | 1915 | 6 December 1917 | Stuttgart, Hofopera 12a | Das Liebesopfer (libretto only, no music completed) | 4 acts | 1917 | | 13 | Der Schmied von Marienburg | 3 acts | 1920 | 16 December 1920 | Rostock, Städtische Bühnen 14 | Rainulf und Adelasia | 3 acts | 1922 | 1923 | Rostock (prelude only) 15 | Die heilige Linde | 3 acts | 1927 | 2001 | Keulen (prelude only) 16 | Wahnopfer | 3 acts | 1928 | 1994 | Rudolstadt, Heidecksburg only libretto and Act 1 finished 17 | Walamund (libretto only, no music completed) | 3 acts | 1928 | | 18 | Das Flüchlein, das Jeder mitbekam | 3 acts | 1929 | 29 April 1984 | Kiel (completed by Hans Peter Mohr)
What is the count of rows and columns in the given table? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_202
WTQ_204-csv_594.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Rank | Nation | Gold | Silver | Bronze | Total 1 | Malaysia | 3 | 0 | 1 | 4 2 | Indonesia | 1 | 3 | 2 | 6 3 | Korea | 1 | 1 | 2 | 4 4 | Thailand | 1 | 0 | 0 | 1 5 | Chinese Taipei | 0 | 1 | 2 | 3 6 | Denmark | 0 | 1 | 0 | 1 7 | Japan | 0 | 0 | 2 | 2 8 | India | 0 | 0 | 1 | 1 9 | Spain | 0 | 0 | 1 | 1
WTQ_for_TSD
Rank | Nation | Gold | Silver | Bronze | Total 1 | Malaysia | 3 | 0 | 1 | 4 2 | Indonesia | 1 | 3 | 2 | 6 3 | Korea | 1 | 1 | 2 | 4 4 | Thailand | 1 | 0 | 0 | 1 5 | Chinese Taipei | 0 | 1 | 2 | 3 6 | Denmark | 0 | 1 | 0 | 1 7 | Japan | 0 | 0 | 2 | 2 8 | India | 0 | 0 | 1 | 1 9 | Spain | 0 | 0 | 1 | 1
This is a table picture. Can you figure out the row and column numbers for this particular table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_203
WTQ_204-csv_134.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Specifications | Foundation | Essentials | Standard | Datacenter Distribution | OEM only | Retail, volume licensing, OEM | Retail, volume licensing, OEM | Volume licensing and OEM Licensing model | Per server | Per server | Per CPU pair + CAL | Per CPU pair + CAL Processor chip limit | 1 | 2 | 64 | 64 Memory limit | 32 GB | 64 GB | 4 TB | 4 TB User limit | 15 | 25 | Unlimited | Unlimited File Services limits | 1 standalone DFS root | 1 standalone DFS root | Unlimited | Unlimited Network Policy and Access Services limits | 50 RRAS connections and 10 IAS connections | 250 RRAS connections, 50 IAS connections, and 2 IAS Server Groups | Unlimited | Unlimited Remote Desktop Services limits | 50 Remote Desktop Services connections | Gateway only | Unlimited | Unlimited Virtualization rights | N/A | Either in 1 VM or 1 physical server, but not both at once | 2 VMs | Unlimited DHCP role | Yes | Yes | Yes | Yes DNS server role | Yes | Yes | Yes | Yes Fax server role | Yes | Yes | Yes | Yes UDDI Services | Yes | Yes | Yes | Yes Print and Document Services | Yes | Yes | Yes | Yes Web Services (Internet Information Services) | Yes | Yes | Yes | Yes Windows Deployment Services | Yes | Yes | Yes | Yes Windows Server Update Services | No | Yes | Yes | Yes Active Directory Lightweight Directory Services | Yes | Yes | Yes | Yes Active Directory Rights Management Services | Yes | Yes | Yes | Yes Application server role | Yes | Yes | Yes | Yes Server Manager | Yes | Yes | Yes | Yes Windows Powershell | Yes | Yes | Yes | Yes Active Directory Domain Services | Must be root of forest and domain | Must be root of forest and domain | Yes | Yes Active Directory Certificate Services | Certificate Authorities only | Certificate Authorities only | Yes | Yes Active Directory Federation Services | Yes | No | Yes | Yes Server Core mode | No | No | Yes | Yes Hyper-V | No | No | Yes | Yes
WTQ_for_TSD
Specifications | Foundation | Essentials | Standard | Datacenter Distribution | OEM only | Retail, volume licensing, OEM | Retail, volume licensing, OEM | Volume licensing and OEM Licensing model | Per server | Per server | Per CPU pair + CAL | Per CPU pair + CAL Processor chip limit | 1 | 2 | 64 | 64 Memory limit | 32 GB | 64 GB | 4 TB | 4 TB User limit | 15 | 25 | Unlimited | Unlimited File Services limits | 1 standalone DFS root | 1 standalone DFS root | Unlimited | Unlimited Network Policy and Access Services limits | 50 RRAS connections and 10 IAS connections | 250 RRAS connections, 50 IAS connections, and 2 IAS Server Groups | Unlimited | Unlimited Remote Desktop Services limits | 50 Remote Desktop Services connections | Gateway only | Unlimited | Unlimited Virtualization rights | N/A | Either in 1 VM or 1 physical server, but not both at once | 2 VMs | Unlimited DHCP role | Yes | Yes | Yes | Yes DNS server role | Yes | Yes | Yes | Yes Fax server role | Yes | Yes | Yes | Yes UDDI Services | Yes | Yes | Yes | Yes Print and Document Services | Yes | Yes | Yes | Yes Web Services (Internet Information Services) | Yes | Yes | Yes | Yes Windows Deployment Services | Yes | Yes | Yes | Yes Windows Server Update Services | No | Yes | Yes | Yes Active Directory Lightweight Directory Services | Yes | Yes | Yes | Yes Active Directory Rights Management Services | Yes | Yes | Yes | Yes Application server role | Yes | Yes | Yes | Yes Server Manager | Yes | Yes | Yes | Yes Windows Powershell | Yes | Yes | Yes | Yes Active Directory Domain Services | Must be root of forest and domain | Must be root of forest and domain | Yes | Yes Active Directory Certificate Services | Certificate Authorities only | Certificate Authorities only | Yes | Yes Active Directory Federation Services | Yes | No | Yes | Yes Server Core mode | No | No | Yes | Yes Hyper-V | No | No | Yes | Yes
This is a table picture. Can you figure out the row and column numbers for this particular table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_204
WTQ_203-csv_658.jpg
Tell me the row and column numbers of the shown table. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Locomotive | Name | Serial No | Entered Service | Livery 9001 | Ernest Henry | 1373/918266-3 | May 94 | FreightCorp 9002 | Michael Wendon | 1374/918266-2 | May 94 | FreightCorp 9003 | Matthew Ryan | 1375/918266-1 | Aug 94 | FreightCorp 9004 | Kevin Nichols | 1376/918266-4 | May 94 | FreightCorp 9005 | Kevin Barry | 1377/918266-5 | May 94 | FreightCorp 9006 | Murray Rose | 1378/918266-6 | May 94 | FreightCorp 9007 | Dunc Gray | 1379/918266-7 | May 94 | FreightCorp 9008 | Ralph Doubell | 1380/918266-8 | Aug 94 | FreightCorp 9009 | Lionel Cox | 1381/918266-9 | Jul 94 | FreightCorp 9010 | John Devitt | 1382/918266-10 | Jul 94 | FreightCorp 9011 | Kevan Gosper | 1383/918266-11 | Jul 94 | FreightCorp 9012 | Neil Brooks/Peter Evans/ Mark Kerry/Mark Tonelli | 1384/918266-12 | Jun 94 | FreightCorp 9013 | Michael Diamond | 1385/918266-13 | Jun 94 | FreightCorp 9014 | Peter Antonie/Stephen Hawkins | 1386/918266-14 | Jul 94 | FreightCorp 9015 | Duncan Armstrong | 1387/918266-15 | Jul 94 | FreightCorp 9016 | Herb Elliott | 1388/918266-16 | Jul 94 | FreightCorp 9017 | Andrew Cooper/Nicholas Green/ Michael McKay/James Tomkins | 1389/918266-17 | Jun 94 | FreightCorp 9018 | John Konrads | 1390/918266-18 | Jul 94 | FreightCorp 9019 | Dean Lukin | 1391/918266-19 | Jul 94 | FreightCorp 9020 | Russell Mark | 1392/918266-20 | Jun 94 | FreightCorp 9021 | Ian O'Brien | 1393/918266-21 | Aug 94 | FreightCorp 9022 | Clint Robinson | 1394/918266-22 | Aug 94 | FreightCorp 9023 | Robert Windle | 1395/918266-23 | Oct 94 | FreightCorp 9024 | John Winter | 1396/918266-24 | Aug 94 | FreightCorp 9025 | Todd Woodbridge/Mark Woodforde | 1397/918266-25 | Aug 94 | FreightCorp 9026 | David Theile | 1398/918266-26 | Oct 94 | FreightCorp 9027 | - | 1399/918266-27 | Aug 94 | FreightCorp 9028 | - | 1400/918266/28 | Aug 94 | FreightCorp 9029 | - | 1401/918266/29 | Aug 94 | FreightCorp 9030 | Australian Men's Hockey Team | 1402/918266-30 | Aug 94 | FreightCorp 9031 | - | 1403/918266/31 | Aug 94 | FreightCorp 9032 | - | 05-1692 | Nov 05 | Pacific National 9033 | - | 05-1693 | Nov 05 | Pacific National 9034 | - | 05-1694 | Nov 05 | Pacific National 9035 | - | 05-1695 | Nov 05 | Pacific National
WTQ_for_TSD
Locomotive | Name | Serial No | Entered Service | Livery 9001 | Ernest Henry | 1373/918266-3 | May 94 | FreightCorp 9002 | Michael Wendon | 1374/918266-2 | May 94 | FreightCorp 9003 | Matthew Ryan | 1375/918266-1 | Aug 94 | FreightCorp 9004 | Kevin Nichols | 1376/918266-4 | May 94 | FreightCorp 9005 | Kevin Barry | 1377/918266-5 | May 94 | FreightCorp 9006 | Murray Rose | 1378/918266-6 | May 94 | FreightCorp 9007 | Dunc Gray | 1379/918266-7 | May 94 | FreightCorp 9008 | Ralph Doubell | 1380/918266-8 | Aug 94 | FreightCorp 9009 | Lionel Cox | 1381/918266-9 | Jul 94 | FreightCorp 9010 | John Devitt | 1382/918266-10 | Jul 94 | FreightCorp 9011 | Kevan Gosper | 1383/918266-11 | Jul 94 | FreightCorp 9012 | Neil Brooks/Peter Evans/ Mark Kerry/Mark Tonelli | 1384/918266-12 | Jun 94 | FreightCorp 9013 | Michael Diamond | 1385/918266-13 | Jun 94 | FreightCorp 9014 | Peter Antonie/Stephen Hawkins | 1386/918266-14 | Jul 94 | FreightCorp 9015 | Duncan Armstrong | 1387/918266-15 | Jul 94 | FreightCorp 9016 | Herb Elliott | 1388/918266-16 | Jul 94 | FreightCorp 9017 | Andrew Cooper/Nicholas Green/ Michael McKay/James Tomkins | 1389/918266-17 | Jun 94 | FreightCorp 9018 | John Konrads | 1390/918266-18 | Jul 94 | FreightCorp 9019 | Dean Lukin | 1391/918266-19 | Jul 94 | FreightCorp 9020 | Russell Mark | 1392/918266-20 | Jun 94 | FreightCorp 9021 | Ian O'Brien | 1393/918266-21 | Aug 94 | FreightCorp 9022 | Clint Robinson | 1394/918266-22 | Aug 94 | FreightCorp 9023 | Robert Windle | 1395/918266-23 | Oct 94 | FreightCorp 9024 | John Winter | 1396/918266-24 | Aug 94 | FreightCorp 9025 | Todd Woodbridge/Mark Woodforde | 1397/918266-25 | Aug 94 | FreightCorp 9026 | David Theile | 1398/918266-26 | Oct 94 | FreightCorp 9027 | - | 1399/918266-27 | Aug 94 | FreightCorp 9028 | - | 1400/918266/28 | Aug 94 | FreightCorp 9029 | - | 1401/918266/29 | Aug 94 | FreightCorp 9030 | Australian Men's Hockey Team | 1402/918266-30 | Aug 94 | FreightCorp 9031 | - | 1403/918266/31 | Aug 94 | FreightCorp 9032 | - | 05-1692 | Nov 05 | Pacific National 9033 | - | 05-1693 | Nov 05 | Pacific National 9034 | - | 05-1694 | Nov 05 | Pacific National 9035 | - | 05-1695 | Nov 05 | Pacific National
Tell me the row and column numbers of the shown table. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_205
WTQ_204-csv_705.jpg
I need to know the count of rows and columns in this specific table. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Rank | Player | Nation | Club | Goals 1 | Jhonny Arteaga | COL | FC New York | 13 2 | Matthew Delicâte | ENG | Richmond Kickers | 10 3 | José Angulo | USA | Harrisburg City Islanders | 9 3 | Maxwell Griffin | USA | Orlando City | 9 3 | Luke Mulholland | ENG | Wilmington Hammerheads | 9 6 | Andriy Budnyy | UKR | Wilmington Hammerheads | 8 6 | Jamie Watson | USA | Orlando City | 8 6 | Andrew Welker | USA | Harrisburg City Islanders | 8 9 | Chris Banks | USA | Wilmington Hammerheads | 7 9 | Sallieu Bundu | SLE | Charlotte Eagles | 7 9 | George Davis IV | USA | Dayton Dutch Lions | 7 9 | Sainey Touray | GAM | Harrisburg City Islanders | 7
WTQ_for_TSD
Rank | Player | Nation | Club | Goals 1 | Jhonny Arteaga | COL | FC New York | 13 2 | Matthew Delicâte | ENG | Richmond Kickers | 10 3 | José Angulo | USA | Harrisburg City Islanders | 9 3 | Maxwell Griffin | USA | Orlando City | 9 3 | Luke Mulholland | ENG | Wilmington Hammerheads | 9 6 | Andriy Budnyy | UKR | Wilmington Hammerheads | 8 6 | Jamie Watson | USA | Orlando City | 8 6 | Andrew Welker | USA | Harrisburg City Islanders | 8 9 | Chris Banks | USA | Wilmington Hammerheads | 7 9 | Sallieu Bundu | SLE | Charlotte Eagles | 7 9 | George Davis IV | USA | Dayton Dutch Lions | 7 9 | Sainey Touray | GAM | Harrisburg City Islanders | 7
I need to know the count of rows and columns in this specific table. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_206
WTQ_203-csv_632.jpg
How many rows and columns does this table have? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Season | Level | Division | Place 1950–97 | | Regional | — 1997/98 | 7 | 2ª Reg. | 5th 1998/99 | 7 | 2ª Reg. | 8th 1999/00 | 7 | 2ª Reg. | 11th 2000/01 | 7 | 2ª Reg. | 8th 2001/02 | 7 | 2ª Reg. | 1st 2002/03 | 6 | 1ª Reg. | 1st 2003/04 | 5 | Reg. Pref. | 6th 2004/05 | 5 | Reg. Pref. | 11th 2005/06 | 5 | Reg. Pref. | 2nd 2006/07 | 4 | 3ª | 8th 2007/08 | 4 | 3ª | 5th 2008/09 | 4 | 3ª | 9th 2009/10 | 4 | 3ª | 14th 2010/11 | 4 | 3ª | 11th 2011/12 | 4 | 3ª | 10th 2012/13 | 4 | 3ª | 9th 2013/14 | 4 | 3ª |
WTQ_for_TSD
Season | Level | Division | Place 1950–97 | | Regional | — 1997/98 | 7 | 2ª Reg. | 5th 1998/99 | 7 | 2ª Reg. | 8th 1999/00 | 7 | 2ª Reg. | 11th 2000/01 | 7 | 2ª Reg. | 8th 2001/02 | 7 | 2ª Reg. | 1st 2002/03 | 6 | 1ª Reg. | 1st 2003/04 | 5 | Reg. Pref. | 6th 2004/05 | 5 | Reg. Pref. | 11th 2005/06 | 5 | Reg. Pref. | 2nd 2006/07 | 4 | 3ª | 8th 2007/08 | 4 | 3ª | 5th 2008/09 | 4 | 3ª | 9th 2009/10 | 4 | 3ª | 14th 2010/11 | 4 | 3ª | 11th 2011/12 | 4 | 3ª | 10th 2012/13 | 4 | 3ª | 9th 2013/14 | 4 | 3ª |
How many rows and columns does this table have? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_207
WTQ_204-csv_619.jpg
Could you count the number of rows and columns in this table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Clerk | Started | Finished | School (year) | Previous clerkship Kenneth W. Dam | 1957 | 1958 | Chicago (1957) | none Alan C. Kohn | 1957 | 1958 | Wash U (1955) | none William C. Canby, Jr. | 1958 | 1959 | Minnesota (1956) | none Heywood H. Davis | 1958 | 1959 | Kansas (1958) | none Jerome B. Libin | 1959 | 1960 | Michigan (1959) | none Patrick F. McCartan | 1959 | 1960 | Notre Dame (1959) | none D. Lawrence Gunnels | 1961 | 1962 | Wash U (1960) | none
WTQ_for_TSD
Clerk | Started | Finished | School (year) | Previous clerkship Kenneth W. Dam | 1957 | 1958 | Chicago (1957) | none Alan C. Kohn | 1957 | 1958 | Wash U (1955) | none William C. Canby, Jr. | 1958 | 1959 | Minnesota (1956) | none Heywood H. Davis | 1958 | 1959 | Kansas (1958) | none Jerome B. Libin | 1959 | 1960 | Michigan (1959) | none Patrick F. McCartan | 1959 | 1960 | Notre Dame (1959) | none D. Lawrence Gunnels | 1961 | 1962 | Wash U (1960) | none
Could you count the number of rows and columns in this table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_208
WTQ_204-csv_656.jpg
This image presents a table, and I'd like to know its row and column numbers. Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Year | State/Territory Men's Division | State/Territory Women's Division | Major Centres Division | Community Division | Women's Division 2012 | Queensland | New South Wales | | | 2012 | New South Wales | New South Wales | Darwin | Brothers in Arms | Bush Potatoes 2011 | New South Wales | New South Wales | Maranoa Murris | Gap Angels | Bush Potatoes 2010 | Western Australia | | | | 2009 | Queensland | | Alkupitja | Tangentyere | New South Wales 2008 | Queensland | | Katherine | Cooktown | New South Wales 2007 | New South Wales | | Alkupitja | Cat Tigers | CGA Cougars 2006 | Queensland | | Alice Springs | Melville Island | Darwin 2005 | Queensland | | Alice Springs | Alkupitja | Darwin 2004 | Queensland | | Alice Springs | Normanton | Tennant Creek 2003 | New South Wales | | Darwin | | 2002 | Northern Territory | | Darwin | | 2001 | Tasmania | | | |
WTQ_for_TSD
Year | State/Territory Men's Division | State/Territory Women's Division | Major Centres Division | Community Division | Women's Division 2012 | Queensland | New South Wales | | | 2012 | New South Wales | New South Wales | Darwin | Brothers in Arms | Bush Potatoes 2011 | New South Wales | New South Wales | Maranoa Murris | Gap Angels | Bush Potatoes 2010 | Western Australia | | | | 2009 | Queensland | | Alkupitja | Tangentyere | New South Wales 2008 | Queensland | | Katherine | Cooktown | New South Wales 2007 | New South Wales | | Alkupitja | Cat Tigers | CGA Cougars 2006 | Queensland | | Alice Springs | Melville Island | Darwin 2005 | Queensland | | Alice Springs | Alkupitja | Darwin 2004 | Queensland | | Alice Springs | Normanton | Tennant Creek 2003 | New South Wales | | Darwin | | 2002 | Northern Territory | | Darwin | | 2001 | Tasmania | | | |
This image presents a table, and I'd like to know its row and column numbers. Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_209
WTQ_203-csv_23.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Year | Title | Rol | Format | Related Links 2010 | Niñas mal (telenovela) | Piti | Telenovela | http://www.novelamtv.com/ 2010 | Soy tu fan (México) | Actor | Serie | https://www.youtube.com/watch?v=hnCb5GG0E2U 2010 | Yo Te Estaré Cuidando | Camilo | Short Film | 2009 | Infinito | | Short Film | 2009 | Me Mueves 2° Temporada | Arturo | Serie | https://www.youtube.com/watch?v=fNE5WHZ_tt8&feature=related 2008 | Me Mueves 1° Temporada | Arturo | Serie | https://www.youtube.com/watch?v=lj2Q6rrOK1k 2008 | La Carretera Es Blanca Y Llana | Peru | Short Film | https://www.youtube.com/watch?v=GKehxHZ16rs 2007 | La Zona | Alejandro | Feature Film | https://www.youtube.com/watch?v=W5SzXJe-NMk 2006–2008 | Skimo | Fito | Serie | https://www.youtube.com/watch?v=w_6cn3BajE0&feature=related 2006 | La Vida Inmune | Malhora | Feature Film | https://www.youtube.com/watch?v=PQt4RU3usnw 2005 | Cuentos De Pelos | | Serie | 2005 | Quinceañera | | Feature Film | 2004 | El Divan De Valentina | Dj | Serie | 2001 | Perros Patinadores | | Short Film | 1997–2001 | Bizbirije | Differentes personajes en \No es Justo\" y \"Ponte Bizbo\"" | Capsulas | https://www.youtube.com/watch?v=M7YCuvFbFJ0
WTQ_for_TSD
Year | Title | Rol | Format | Related Links 2010 | Niñas mal (telenovela) | Piti | Telenovela | http://www.novelamtv.com/ 2010 | Soy tu fan (México) | Actor | Serie | https://www.youtube.com/watch?v=hnCb5GG0E2U 2010 | Yo Te Estaré Cuidando | Camilo | Short Film | 2009 | Infinito | | Short Film | 2009 | Me Mueves 2° Temporada | Arturo | Serie | https://www.youtube.com/watch?v=fNE5WHZ_tt8&feature=related 2008 | Me Mueves 1° Temporada | Arturo | Serie | https://www.youtube.com/watch?v=lj2Q6rrOK1k 2008 | La Carretera Es Blanca Y Llana | Peru | Short Film | https://www.youtube.com/watch?v=GKehxHZ16rs 2007 | La Zona | Alejandro | Feature Film | https://www.youtube.com/watch?v=W5SzXJe-NMk 2006–2008 | Skimo | Fito | Serie | https://www.youtube.com/watch?v=w_6cn3BajE0&feature=related 2006 | La Vida Inmune | Malhora | Feature Film | https://www.youtube.com/watch?v=PQt4RU3usnw 2005 | Cuentos De Pelos | | Serie | 2005 | Quinceañera | | Feature Film | 2004 | El Divan De Valentina | Dj | Serie | 2001 | Perros Patinadores | | Short Film | 1997–2001 | Bizbirije | Differentes personajes en \No es Justo\" y \"Ponte Bizbo\"" | Capsulas | https://www.youtube.com/watch?v=M7YCuvFbFJ0
This is a table picture. Can you figure out the row and column numbers for this particular table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_210
WTQ_202-csv_248.jpg
What is the count of rows and columns in the given table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Year | Film | Role | Notes 1971 | The Devils | Phillippe | 1971 | The Boy Friend | Fay | 1972 | Eagle in a Cage | Betty Balcombe | 1973 | The Love Ban | Joyce | 1974 | Mahler | Alma Mahler | Received BAFTA Award for Most Promising Newcomer 1974 | Butley | Carol Heasman | 1975 | Lisztomania | | Uncredited Appearance 1976 | Voyage of the Damned | Lotte Schulman | 1977 | Valentino | | Uncredited Appearance 1978 | Sweeney 2 | Switchboard Girl | 1979 | The World Is Full of Married Men | Lori Grossman | 1980 | The Watcher in the Woods | Young Mrs Aylwood | 1980 | McVicar | Kate | 1986 | Castaway | Sister Saint Margaret | 1994 | Beyond Bedlam | Sister Romulus | 1995 | Jackson: My Life... Your Fault | Josephine | 1997 | Preaching to the Perverted | Miss Wilderspin | 2002 | AKA | Elizabeth of Lithuania | 2005 | Mrs Palfrey at the Claremont | Shirley Burton | 2011 | Cockneys vs Zombies | Doreen | 2013 | Still Waters | Grandma | In Production
WTQ_for_TSD
Year | Film | Role | Notes 1971 | The Devils | Phillippe | 1971 | The Boy Friend | Fay | 1972 | Eagle in a Cage | Betty Balcombe | 1973 | The Love Ban | Joyce | 1974 | Mahler | Alma Mahler | Received BAFTA Award for Most Promising Newcomer 1974 | Butley | Carol Heasman | 1975 | Lisztomania | | Uncredited Appearance 1976 | Voyage of the Damned | Lotte Schulman | 1977 | Valentino | | Uncredited Appearance 1978 | Sweeney 2 | Switchboard Girl | 1979 | The World Is Full of Married Men | Lori Grossman | 1980 | The Watcher in the Woods | Young Mrs Aylwood | 1980 | McVicar | Kate | 1986 | Castaway | Sister Saint Margaret | 1994 | Beyond Bedlam | Sister Romulus | 1995 | Jackson: My Life... Your Fault | Josephine | 1997 | Preaching to the Perverted | Miss Wilderspin | 2002 | AKA | Elizabeth of Lithuania | 2005 | Mrs Palfrey at the Claremont | Shirley Burton | 2011 | Cockneys vs Zombies | Doreen | 2013 | Still Waters | Grandma | In Production
What is the count of rows and columns in the given table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_211
WTQ_204-csv_165.jpg
This image presents a table, and I'd like to know its row and column numbers. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Rank | Nation | Gold | Silver | Bronze | Total 1 | France | 11 | 5 | 3 | 19 2 | Greece | 6 | 7 | 6 | 19 3 | Yugoslavia | 3 | 2 | 1 | 6 4 | Spain | 1 | 5 | 5 | 11 5 | Morocco | 1 | 1 | 0 | 2 5 | Turkey | 1 | 1 | 0 | 2 7 | Egypt | 0 | 1 | 7 | 8 8 | Tunisia | 0 | 1 | 0 | 1 Totaal | Totaal | 23 | 23 | 22 | 68
WTQ_for_TSD
Rank | Nation | Gold | Silver | Bronze | Total 1 | France | 11 | 5 | 3 | 19 2 | Greece | 6 | 7 | 6 | 19 3 | Yugoslavia | 3 | 2 | 1 | 6 4 | Spain | 1 | 5 | 5 | 11 5 | Morocco | 1 | 1 | 0 | 2 5 | Turkey | 1 | 1 | 0 | 2 7 | Egypt | 0 | 1 | 7 | 8 8 | Tunisia | 0 | 1 | 0 | 1 Totaal | Totaal | 23 | 23 | 22 | 68
This image presents a table, and I'd like to know its row and column numbers. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_212
WTQ_203-csv_626.jpg
What is the count of rows and columns in the given table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Rank | Mountain Peak | Nation | Province | Elevation | Prominence | Isolation 1 | Volcán Tajumulco PB | Guatemala | San Marcos | 4220 m 13,845 ft | 3980 m 13,058 ft | 722 km 448 mi 2 | Chirripó Grande PB | Costa Rica | Cartago Limón San José | 3819 m 12,530 ft | 3726 m 12,224 ft | 864 km 537 mi 3 | Montaña de Santa Bárbara PB | Honduras | Santa Bárbara | 2744 m 9,003 ft | 2084 m 6,837 ft | 74 km 46 mi 4 | Cerro las Minas PB | Honduras | Lempira | 2849 m 9,347 ft | 2069 m 6,788 ft | 130 km 81 mi 5 | Volcán de Agua PB | Guatemala | Escuintla Sacatepéquez | 3761 m 12,339 ft | 1981 m 6,499 ft | 16 km 10 mi 6 | Alto Cuchumatanes PB | Guatemala | Huehuetenango | 3837 m 12,589 ft | 1877 m 6,158 ft | 65 km 40 mi 7 | Volcán Irazú PB | Costa Rica | Cartago San José | 3402 m 11,161 ft | 1872 m 6,142 ft | 48 km 30 mi 8 | Montañas Peña Blanca High Point PB | Guatemala | Huehuetenango | 3518 m 11,542 ft | 1858 m 6,096 ft | 42 km 26 mi 9 | Volcán Acatenango PB | Guatemala | Chimaltenango Sacatepéquez | 3975 m 13,041 ft | 1835 m 6,020 ft | 126 km 78 mi 10 | Volcán San Miguel PB | El Salvador | San Miguel | 2131 m 6,991 ft | 1831 m 6,007 ft | 64 km 40 mi 11 | Cerro Tacarcuna PB | Panama | Darién | 1875 m 6,152 ft | 1770 m 5,807 ft | 99 km 61 mi 12 | Volcán Atitlán PB | Guatemala | Sololá | 3537 m 11,604 ft | 1754 m 5,755 ft | 35 km 21 mi 13 | Pico Bonito PB | Honduras | Atlántida | 2450 m 8,038 ft | 1710 m 5,610 ft | 152 km 95 mi 14 | Montaña San Ildefonso PB | Honduras | Cortés | 2242 m 7,356 ft | 1702 m 5,584 ft | 68 km 42 mi 15 | Volcán San Cristóbal PB | Nicaragua | Chinandega | 1745 m 5,725 ft | 1665 m 5,463 ft | 134 km 83 mi
WTQ_for_TSD
Rank | Mountain Peak | Nation | Province | Elevation | Prominence | Isolation 1 | Volcán Tajumulco PB | Guatemala | San Marcos | 4220 m 13,845 ft | 3980 m 13,058 ft | 722 km 448 mi 2 | Chirripó Grande PB | Costa Rica | Cartago Limón San José | 3819 m 12,530 ft | 3726 m 12,224 ft | 864 km 537 mi 3 | Montaña de Santa Bárbara PB | Honduras | Santa Bárbara | 2744 m 9,003 ft | 2084 m 6,837 ft | 74 km 46 mi 4 | Cerro las Minas PB | Honduras | Lempira | 2849 m 9,347 ft | 2069 m 6,788 ft | 130 km 81 mi 5 | Volcán de Agua PB | Guatemala | Escuintla Sacatepéquez | 3761 m 12,339 ft | 1981 m 6,499 ft | 16 km 10 mi 6 | Alto Cuchumatanes PB | Guatemala | Huehuetenango | 3837 m 12,589 ft | 1877 m 6,158 ft | 65 km 40 mi 7 | Volcán Irazú PB | Costa Rica | Cartago San José | 3402 m 11,161 ft | 1872 m 6,142 ft | 48 km 30 mi 8 | Montañas Peña Blanca High Point PB | Guatemala | Huehuetenango | 3518 m 11,542 ft | 1858 m 6,096 ft | 42 km 26 mi 9 | Volcán Acatenango PB | Guatemala | Chimaltenango Sacatepéquez | 3975 m 13,041 ft | 1835 m 6,020 ft | 126 km 78 mi 10 | Volcán San Miguel PB | El Salvador | San Miguel | 2131 m 6,991 ft | 1831 m 6,007 ft | 64 km 40 mi 11 | Cerro Tacarcuna PB | Panama | Darién | 1875 m 6,152 ft | 1770 m 5,807 ft | 99 km 61 mi 12 | Volcán Atitlán PB | Guatemala | Sololá | 3537 m 11,604 ft | 1754 m 5,755 ft | 35 km 21 mi 13 | Pico Bonito PB | Honduras | Atlántida | 2450 m 8,038 ft | 1710 m 5,610 ft | 152 km 95 mi 14 | Montaña San Ildefonso PB | Honduras | Cortés | 2242 m 7,356 ft | 1702 m 5,584 ft | 68 km 42 mi 15 | Volcán San Cristóbal PB | Nicaragua | Chinandega | 1745 m 5,725 ft | 1665 m 5,463 ft | 134 km 83 mi
What is the count of rows and columns in the given table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_213
WTQ_203-csv_785.jpg
For the shown table, how many rows and columns are there? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Year | Title | Role | Notes 1991 | Flesh'n Blood | Penelope | 1 episode 1992 | True Colors | Lorae | 1 episode 1994 | The All-New Mickey Mouse (MMC) | Herself | 1 episode 1994–1999 | Sister, Sister | Tamera Campbell | 119 episodes 1995 | Are You Afraid of the Dark? | Evil Chameleon | 1 episode 1995–1996 | The Adventures of Hyperman | Emma C. Squared | 8 episodes 1996 | All That | Herself | 1997 | Smart Guy | Roxanne | 1 episode 1998 | Blues Clues | Herself | 1 episode 1999 | Detention | Orangejella LaBelle | 13 episodes 2000 | How I Loved a Macho Boy | Jamal Santos | 3 episodes 2004–2006 | Strong Medicine | Dr. Kayla Thorton | 37 episodes 2006–2007 | Family Guy | Esther | Voice 3 episodes 2009 | Roommates | Hope | 13 episodes 2009 | The Super Hero Squad Show | Misty Knight | 1 episode 2011 | Things We Do for Love | Lourdes | 5 episodes 2011 | Access Hollywood Live | Herself | Co-host 2011 | CHRISJayify | Herself | Episode: \Drugs Are Bad\"" 2011–2013 | Tia & Tamera | Herself | Executive producer 2012 | Christmas Angel | Daphney | 2013 | The Real | Herself | Host 2014 | Melissa and Joey | Gillian | Season 3 Episode 24 'To Tell the Truth'
WTQ_for_TSD
Year | Title | Role | Notes 1991 | Flesh'n Blood | Penelope | 1 episode 1992 | True Colors | Lorae | 1 episode 1994 | The All-New Mickey Mouse (MMC) | Herself | 1 episode 1994–1999 | Sister, Sister | Tamera Campbell | 119 episodes 1995 | Are You Afraid of the Dark? | Evil Chameleon | 1 episode 1995–1996 | The Adventures of Hyperman | Emma C. Squared | 8 episodes 1996 | All That | Herself | 1997 | Smart Guy | Roxanne | 1 episode 1998 | Blues Clues | Herself | 1 episode 1999 | Detention | Orangejella LaBelle | 13 episodes 2000 | How I Loved a Macho Boy | Jamal Santos | 3 episodes 2004–2006 | Strong Medicine | Dr. Kayla Thorton | 37 episodes 2006–2007 | Family Guy | Esther | Voice 3 episodes 2009 | Roommates | Hope | 13 episodes 2009 | The Super Hero Squad Show | Misty Knight | 1 episode 2011 | Things We Do for Love | Lourdes | 5 episodes 2011 | Access Hollywood Live | Herself | Co-host 2011 | CHRISJayify | Herself | Episode: \Drugs Are Bad\"" 2011–2013 | Tia & Tamera | Herself | Executive producer 2012 | Christmas Angel | Daphney | 2013 | The Real | Herself | Host 2014 | Melissa and Joey | Gillian | Season 3 Episode 24 'To Tell the Truth'
For the shown table, how many rows and columns are there? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_214
WTQ_203-csv_236.jpg
I'd like to know the total number of rows and columns in the provided table. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Leg | Stage | Time | Name | Length | Winner | Time | Avg. spd. | Rally leader 1 (16 Feb) | SS1 | 07:43 | Loten 1 | 30.30 km | M. Hirvonen | 16:14.1 | 111.98 km/h | M. Hirvonen 1 (16 Feb) | SS2 | 08:34 | Haslemoen | 11.92 km | S. Loeb | 8:08.4 | 87.86 km/h | M. Hirvonen 1 (16 Feb) | SS3 | 11:24 | Loten 2 | 30.30 km | M. Hirvonen | 16:09.9 | 112.47 km/h | M. Hirvonen 1 (16 Feb) | SS4 | 12:30 | Grue | 14.36 km | S. Loeb | 7:31.8 | 114.42 km/h | M. Hirvonen 1 (16 Feb) | SS5 | 13:52 | Opaker | 14.64 km | J. Latvala | 7:59.8 | 109.85 km/h | M. Hirvonen 1 (16 Feb) | SS6 | 14:36 | Kongsvinger | 14.60 km | S. Loeb | 9:44.5 | 89.92 km/h | M. Hirvonen 1 (16 Feb) | SS7 | 15:30 | Finnskogen | 21.29 km | S. Loeb | 12:42.3 | 100.54 km/h | M. Hirvonen 1 (16 Feb) | SS8 | 16:33 | Kirkanaer | 6.75 km | S. Loeb | 5:48.9 | 69.65 km/h | M. Hirvonen 2 (17 Feb) | SS9 | 08:09 | Eleverum 1 | 44.27 km | M. Hirvonen | 24:40.3 | 107.66 km/h | M. Hirvonen 2 (17 Feb) | SS10 | 09:23 | Terningmoen | 12.71 km | D. Sordo | 7:59.1 | 95.5 km/h | M. Hirvonen 2 (17 Feb) | SS11 | 12:05 | Mountain 1 | 24.36 km | M. Hirvonen | 14:01.8 | 104.18 km/h | M. Hirvonen 2 (17 Feb) | SS12 | 13:06 | Lillehammar | 5.98 km | M. Grönholm | 4:33.9 | 78.6 km/h | M. Hirvonen 2 (17 Feb) | SS13 | 14:00 | Ringsaker 1 | 27.30 km | M. Grönholm | 16:29.7 | 99.3 km/h | M. Hirvonen 2 (17 Feb) | SS14 | 15:10 | Hamar 1 | 1.14 km | M. Grönholm | 1:13.8 | 55.61 km/h | M. Hirvonen 3 (18 Feb) | SS15 | 08:08 | Mountain 2 | 24.36 km | S. Loeb | 13:18.2 | 109.87 km/h | M. Hirvonen 3 (18 Feb) | SS16 | 08:55 | Ringsaker 2 | 27.30 km | H. Solberg | 15:28.6 | 105.84 km/h | M. Hirvonen 3 (18 Feb) | SS17 | 10:05 | Hamar 2 | 1.14 km | X. Pons S. Loeb P. Solberg | 1:11.8 | 57.16 km/h | M. Hirvonen 3 (18 Feb) | SS18 | 12:14 | Eleverum 2 | 44.27 km | M. Grönholm | 24:10.3 | 109.89 km/h | M. Hirvonen
WTQ_for_TSD
Leg | Stage | Time | Name | Length | Winner | Time | Avg. spd. | Rally leader 1 (16 Feb) | SS1 | 07:43 | Loten 1 | 30.30 km | M. Hirvonen | 16:14.1 | 111.98 km/h | M. Hirvonen 1 (16 Feb) | SS2 | 08:34 | Haslemoen | 11.92 km | S. Loeb | 8:08.4 | 87.86 km/h | M. Hirvonen 1 (16 Feb) | SS3 | 11:24 | Loten 2 | 30.30 km | M. Hirvonen | 16:09.9 | 112.47 km/h | M. Hirvonen 1 (16 Feb) | SS4 | 12:30 | Grue | 14.36 km | S. Loeb | 7:31.8 | 114.42 km/h | M. Hirvonen 1 (16 Feb) | SS5 | 13:52 | Opaker | 14.64 km | J. Latvala | 7:59.8 | 109.85 km/h | M. Hirvonen 1 (16 Feb) | SS6 | 14:36 | Kongsvinger | 14.60 km | S. Loeb | 9:44.5 | 89.92 km/h | M. Hirvonen 1 (16 Feb) | SS7 | 15:30 | Finnskogen | 21.29 km | S. Loeb | 12:42.3 | 100.54 km/h | M. Hirvonen 1 (16 Feb) | SS8 | 16:33 | Kirkanaer | 6.75 km | S. Loeb | 5:48.9 | 69.65 km/h | M. Hirvonen 2 (17 Feb) | SS9 | 08:09 | Eleverum 1 | 44.27 km | M. Hirvonen | 24:40.3 | 107.66 km/h | M. Hirvonen 2 (17 Feb) | SS10 | 09:23 | Terningmoen | 12.71 km | D. Sordo | 7:59.1 | 95.5 km/h | M. Hirvonen 2 (17 Feb) | SS11 | 12:05 | Mountain 1 | 24.36 km | M. Hirvonen | 14:01.8 | 104.18 km/h | M. Hirvonen 2 (17 Feb) | SS12 | 13:06 | Lillehammar | 5.98 km | M. Grönholm | 4:33.9 | 78.6 km/h | M. Hirvonen 2 (17 Feb) | SS13 | 14:00 | Ringsaker 1 | 27.30 km | M. Grönholm | 16:29.7 | 99.3 km/h | M. Hirvonen 2 (17 Feb) | SS14 | 15:10 | Hamar 1 | 1.14 km | M. Grönholm | 1:13.8 | 55.61 km/h | M. Hirvonen 3 (18 Feb) | SS15 | 08:08 | Mountain 2 | 24.36 km | S. Loeb | 13:18.2 | 109.87 km/h | M. Hirvonen 3 (18 Feb) | SS16 | 08:55 | Ringsaker 2 | 27.30 km | H. Solberg | 15:28.6 | 105.84 km/h | M. Hirvonen 3 (18 Feb) | SS17 | 10:05 | Hamar 2 | 1.14 km | X. Pons S. Loeb P. Solberg | 1:11.8 | 57.16 km/h | M. Hirvonen 3 (18 Feb) | SS18 | 12:14 | Eleverum 2 | 44.27 km | M. Grönholm | 24:10.3 | 109.89 km/h | M. Hirvonen
I'd like to know the total number of rows and columns in the provided table. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_215
WTQ_203-csv_86.jpg
This image displays a table. Could you provide me with the row number and column number corresponding to this table? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> Rank | Player Name | No. of Titles | Runner-up | Final Appearances 1 | Jansher Khan | 8 | 1 | 9 2 | Jahangir Khan | 6 | 3 | 9 3 | Geoff Hunt | 4 | 1 | 5 4 | Amr Shabana | 4 | 0 | 4 5 | Nick Matthew | 3 | 0 | 3 6 | Ramy Ashour | 2 | 1 | 3 6 | David Palmer | 2 | 1 | 3 8 | Peter Nicol | 1 | 2 | 3 9 | Rodney Eyles | 1 | 1 | 2 9 | Thierry Lincou | 1 | 1 | 2 9 | Ross Norman | 1 | 1 | 2 12 | Rodney Martin | 1 | 0 | 1 12 | Jonathon Power | 1 | 0 | 1 14 | Chris Dittmar | 0 | 5 | 5 15 | Grégory Gaultier | 0 | 4 | 4 15 | Qamar Zaman | 0 | 4 | 4 17 | Ahmed Barada | 0 | 1 | 1 17 | Lee Beachill | 0 | 1 | 1 17 | Karim Darwish | 0 | 1 | 1 17 | Mohamed El Shorbagy | 0 | 1 | 1 17 | Del Harris | 0 | 1 | 1 17 | Mohibullah Khan | 0 | 1 | 1 17 | Peter Marshall | 0 | 1 | 1 17 | John White | 0 | 1 | 1 17 | Dean Williams | 0 | 1 | 1 17 | James Willstrop | 0 | 1 | 1
WTQ_for_TSD
Rank | Player Name | No. of Titles | Runner-up | Final Appearances 1 | Jansher Khan | 8 | 1 | 9 2 | Jahangir Khan | 6 | 3 | 9 3 | Geoff Hunt | 4 | 1 | 5 4 | Amr Shabana | 4 | 0 | 4 5 | Nick Matthew | 3 | 0 | 3 6 | Ramy Ashour | 2 | 1 | 3 6 | David Palmer | 2 | 1 | 3 8 | Peter Nicol | 1 | 2 | 3 9 | Rodney Eyles | 1 | 1 | 2 9 | Thierry Lincou | 1 | 1 | 2 9 | Ross Norman | 1 | 1 | 2 12 | Rodney Martin | 1 | 0 | 1 12 | Jonathon Power | 1 | 0 | 1 14 | Chris Dittmar | 0 | 5 | 5 15 | Grégory Gaultier | 0 | 4 | 4 15 | Qamar Zaman | 0 | 4 | 4 17 | Ahmed Barada | 0 | 1 | 1 17 | Lee Beachill | 0 | 1 | 1 17 | Karim Darwish | 0 | 1 | 1 17 | Mohamed El Shorbagy | 0 | 1 | 1 17 | Del Harris | 0 | 1 | 1 17 | Mohibullah Khan | 0 | 1 | 1 17 | Peter Marshall | 0 | 1 | 1 17 | John White | 0 | 1 | 1 17 | Dean Williams | 0 | 1 | 1 17 | James Willstrop | 0 | 1 | 1
This image displays a table. Could you provide me with the row number and column number corresponding to this table? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_216
WTQ_204-csv_844.jpg
Please ascertain the quantity of rows and columns within the provided table. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Rank | Athlete | Nationality | 2.15 | 2.20 | 2.24 | 2.27 | Result | Notes 1. | Yaroslav Rybakov | Russia | o | o | o | o | 2.27 | q 1. | Andriy Sokolovskyy | Ukraine | o | o | o | o | 2.27 | q 1. | Stefan Holm | Sweden | o | o | o | o | 2.27 | q 1. | Andrey Tereshin | Russia | o | o | o | o | 2.27 | q 1. | Víctor Moya | Cuba | o | o | o | o | 2.27 | q, PB 1. | Linus Thörnblad | Sweden | o | o | o | o | 2.27 | q 7. | Giulio Ciotti | Italy | o | o | o | xxx | 2.24 | q 8. | Robert Wolski | Poland | xo | o | o | xxx | 2.24 | q 9. | Ramsay Carelse | South Africa | xo | xo | o | xxx | 2.24 | 10. | Tora Harris | United States | o | o | xo | xxx | 2.24 | 10. | Nicola Ciotti | Italy | o | o | xo | xxx | 2.24 | 10. | Wojciech Theiner | Poland | o | o | xo | xxx | 2.24 | 13. | Tomáš Janku | Czech Republic | o | o | xxo | xxx | 2.24 | 13. | Mustapha Raifak | France | o | o | xxo | xxx | 2.24 | 15. | Svatoslav Ton | Czech Republic | o | xo | xxx | | 2.20 | 16. | Adam Shunk | United States | o | xxx | | 2.15 | | 16. | Roman Fricke | Germany | o | xxx | | 2.15 | |
WTQ_for_TSD
Rank | Athlete | Nationality | 2.15 | 2.20 | 2.24 | 2.27 | Result | Notes 1. | Yaroslav Rybakov | Russia | o | o | o | o | 2.27 | q 1. | Andriy Sokolovskyy | Ukraine | o | o | o | o | 2.27 | q 1. | Stefan Holm | Sweden | o | o | o | o | 2.27 | q 1. | Andrey Tereshin | Russia | o | o | o | o | 2.27 | q 1. | Víctor Moya | Cuba | o | o | o | o | 2.27 | q, PB 1. | Linus Thörnblad | Sweden | o | o | o | o | 2.27 | q 7. | Giulio Ciotti | Italy | o | o | o | xxx | 2.24 | q 8. | Robert Wolski | Poland | xo | o | o | xxx | 2.24 | q 9. | Ramsay Carelse | South Africa | xo | xo | o | xxx | 2.24 | 10. | Tora Harris | United States | o | o | xo | xxx | 2.24 | 10. | Nicola Ciotti | Italy | o | o | xo | xxx | 2.24 | 10. | Wojciech Theiner | Poland | o | o | xo | xxx | 2.24 | 13. | Tomáš Janku | Czech Republic | o | o | xxo | xxx | 2.24 | 13. | Mustapha Raifak | France | o | o | xxo | xxx | 2.24 | 15. | Svatoslav Ton | Czech Republic | o | xo | xxx | | 2.20 | 16. | Adam Shunk | United States | o | xxx | | 2.15 | | 16. | Roman Fricke | Germany | o | xxx | | 2.15 | |
Please ascertain the quantity of rows and columns within the provided table. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_217
WTQ_204-csv_464.jpg
I need to know the count of rows and columns in this specific table. The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> Year | Model | Denomination | Metal composition | Dimensions 1992 | Re-establishment of kroon, 28 August 1992 | 100 krooni | .900 silver | 23 grams (0.81 oz)36 millimetres (1.4 in) 1996 | Atlanta Olympics, 100th anniversary of Modern Olympiad | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1998 | 80th anniversary of declaration of Independence, 1918–1998 | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1992 | Re-establishment of Krooni currency | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1992 | Barcelona Olympics | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1998 | 80th anniversary of declaration of Independence, 1918–1998 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 2002 | 370th anniversary of the founding of Tartu University | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 2004 | The Flag of Estonia – 2004 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in)
WTQ_for_TSD
Year | Model | Denomination | Metal composition | Dimensions 1992 | Re-establishment of kroon, 28 August 1992 | 100 krooni | .900 silver | 23 grams (0.81 oz)36 millimetres (1.4 in) 1996 | Atlanta Olympics, 100th anniversary of Modern Olympiad | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1998 | 80th anniversary of declaration of Independence, 1918–1998 | 100 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1992 | Re-establishment of Krooni currency | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1992 | Barcelona Olympics | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 1998 | 80th anniversary of declaration of Independence, 1918–1998 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 2002 | 370th anniversary of the founding of Tartu University | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in) 2004 | The Flag of Estonia – 2004 | 10 krooni | .925 silver | 25 grams (0.88 oz)38 millimetres (1.5 in)
I need to know the count of rows and columns in this specific table. The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_218
WTQ_204-csv_67.jpg
For the shown table, how many rows and columns are there? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> # | Stadium | Capacity | City | Region | Home Team | Opened 1 | Stade de France | 81,338 | Paris | Île-de-France | France national football team | 1998 2 | Stade Vélodrome | 60,013 | Marseille | Provence-Alpes-Côte d'Azur | Olympique de Marseille | 1937 3 | Grand Stade Lille Métropole | 50,186 | Villeneuve-d'Ascq | Nord-Pas-de-Calais | Lille OSC | 2012 4 | Parc des Princes | 48,712 | Paris | Île-de-France | Paris Saint-Germain FC | 1897 5 | Stade Félix Bollaert | 41,233 | Lens | Nord-Pas-de-Calais | RC Lens | 1932 6 | Stade Gerland | 41,044 | Lyon | Rhône-Alpes | Olympique Lyonnais | 1926 7 | Stade de la Beaujoire | 38,285 | Nantes | Pays de la Loire | FC Nantes Atlantique | 1984 8 | Stade Geoffroy-Guichard | 37,587 | Saint-Étienne | Rhône-Alpes | AS Saint-Étienne | 1931 9 | Allianz Riviera | 35,624 | Nice | Provence-Alpes-Côte d'Azur | OGC Nice | 2013 10 | Stadium Municipal | 35,575 | Toulouse | Midi-Pyrénées | Toulouse FC | 1937 11 | Stade Chaban-Delmas | 34,462 | Bordeaux | Aquitaine | FC Girondins de Bordeaux | 1938 12 | Stade de la Mosson | 32,939 | Montpellier | Languedoc-Roussillon | Montpellier HSC | 1972 13 | Stade de la Route de Lorient | 31,127 | Rennes | Brittany | Stade Rennais FC | 1912 14 | Stade de la Meinau | 29,230 | Strasbourg | Alsace | RC Strasbourg | 1914 15 | Stade Municipal Saint-Symphorien | 26,700 | Metz | Lorraine | FC Metz | 1923 16 | Grand Stade du Havre | 25,178 | Le Havre | Upper Normandy | Le Havre AC | 2012 17 | MMArena | 25,000 | Le Mans | Pays de la Loire | Le Mans UC | 2011 18 | Stade du Hainaut | 24,926 | Valenciennes | Nord-Pas-de-Calais | Valenciennes FC | 2011 19 | Stade de l'Abbé-Deschamps | 23,467 | Auxerre | Bourgogne | AJ Auxerre | 1918 20 | Stade Louis Dugauguez | 23,189 | Sedan | Champagne-Ardenne | Club Sportif Sedan Ardennes | 2000 21 | Stade Auguste-Delaune | 21,684 | Reims | Champagne-Ardenne | Stade Reims | 1935 22 | Stade Michel d'Ornano | 21,500 | Caen | Lower Normandy | Stade Malherbe Caen | 1993 23 | Stade de l'Aube | 20,400 | Troyes | Champagne-Ardenne | Troyes AC | 1956 24 | Stade Marcel Picot | 20,087 | Tomblaine | Lorraine | AS Nancy | 1926 25 | Stade des Alpes | 20,068 | Grenoble | Rhône-Alpes | Grenoble Foot 38 | 2008 26 | Stade Auguste Bonal | 20,025 | Montbéliard | Franche-Comté | FC Sochaux-Montbéliard | 2000 27 | Stade Sébastien Charléty | 20,000 | Paris | Île-de-France | Paris FC | 1938
WTQ_for_TSD
# | Stadium | Capacity | City | Region | Home Team | Opened 1 | Stade de France | 81,338 | Paris | Île-de-France | France national football team | 1998 2 | Stade Vélodrome | 60,013 | Marseille | Provence-Alpes-Côte d'Azur | Olympique de Marseille | 1937 3 | Grand Stade Lille Métropole | 50,186 | Villeneuve-d'Ascq | Nord-Pas-de-Calais | Lille OSC | 2012 4 | Parc des Princes | 48,712 | Paris | Île-de-France | Paris Saint-Germain FC | 1897 5 | Stade Félix Bollaert | 41,233 | Lens | Nord-Pas-de-Calais | RC Lens | 1932 6 | Stade Gerland | 41,044 | Lyon | Rhône-Alpes | Olympique Lyonnais | 1926 7 | Stade de la Beaujoire | 38,285 | Nantes | Pays de la Loire | FC Nantes Atlantique | 1984 8 | Stade Geoffroy-Guichard | 37,587 | Saint-Étienne | Rhône-Alpes | AS Saint-Étienne | 1931 9 | Allianz Riviera | 35,624 | Nice | Provence-Alpes-Côte d'Azur | OGC Nice | 2013 10 | Stadium Municipal | 35,575 | Toulouse | Midi-Pyrénées | Toulouse FC | 1937 11 | Stade Chaban-Delmas | 34,462 | Bordeaux | Aquitaine | FC Girondins de Bordeaux | 1938 12 | Stade de la Mosson | 32,939 | Montpellier | Languedoc-Roussillon | Montpellier HSC | 1972 13 | Stade de la Route de Lorient | 31,127 | Rennes | Brittany | Stade Rennais FC | 1912 14 | Stade de la Meinau | 29,230 | Strasbourg | Alsace | RC Strasbourg | 1914 15 | Stade Municipal Saint-Symphorien | 26,700 | Metz | Lorraine | FC Metz | 1923 16 | Grand Stade du Havre | 25,178 | Le Havre | Upper Normandy | Le Havre AC | 2012 17 | MMArena | 25,000 | Le Mans | Pays de la Loire | Le Mans UC | 2011 18 | Stade du Hainaut | 24,926 | Valenciennes | Nord-Pas-de-Calais | Valenciennes FC | 2011 19 | Stade de l'Abbé-Deschamps | 23,467 | Auxerre | Bourgogne | AJ Auxerre | 1918 20 | Stade Louis Dugauguez | 23,189 | Sedan | Champagne-Ardenne | Club Sportif Sedan Ardennes | 2000 21 | Stade Auguste-Delaune | 21,684 | Reims | Champagne-Ardenne | Stade Reims | 1935 22 | Stade Michel d'Ornano | 21,500 | Caen | Lower Normandy | Stade Malherbe Caen | 1993 23 | Stade de l'Aube | 20,400 | Troyes | Champagne-Ardenne | Troyes AC | 1956 24 | Stade Marcel Picot | 20,087 | Tomblaine | Lorraine | AS Nancy | 1926 25 | Stade des Alpes | 20,068 | Grenoble | Rhône-Alpes | Grenoble Foot 38 | 2008 26 | Stade Auguste Bonal | 20,025 | Montbéliard | Franche-Comté | FC Sochaux-Montbéliard | 2000 27 | Stade Sébastien Charléty | 20,000 | Paris | Île-de-France | Paris FC | 1938
For the shown table, how many rows and columns are there? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_219
WTQ_202-csv_17.jpg
Please determine the total count of rows and columns in the provided table, respectively. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Date | Label | Format | Country | Catalog | Notes November 10, 1969 | Columbia | LP | US | CS 9942 | Original release. January 16, 1970 | CBS | LP | UK | S 63795 | Original release. 1982 | Embassy | LP | UK | EMB 31956 | 1989 | Columbia | CD | US | CK 9942 | Original CD release. March 25, 1997 | Columbia/Legacy | CD | US | CK 65114 | Reissue containing seven bonus tracks and the remastered stereo album. March 25, 1997 | Columbia/Legacy | CD | UK | COL 486754 | Reissue containing seven bonus tracks and the remastered stereo album. 2003 | Sony | CD | Japan | MHCP-102 | Reissue containing seven bonus tracks and the remastered album in a replica LP sleeve.
WTQ_for_TSD
Date | Label | Format | Country | Catalog | Notes November 10, 1969 | Columbia | LP | US | CS 9942 | Original release. January 16, 1970 | CBS | LP | UK | S 63795 | Original release. 1982 | Embassy | LP | UK | EMB 31956 | 1989 | Columbia | CD | US | CK 9942 | Original CD release. March 25, 1997 | Columbia/Legacy | CD | US | CK 65114 | Reissue containing seven bonus tracks and the remastered stereo album. March 25, 1997 | Columbia/Legacy | CD | UK | COL 486754 | Reissue containing seven bonus tracks and the remastered stereo album. 2003 | Sony | CD | Japan | MHCP-102 | Reissue containing seven bonus tracks and the remastered album in a replica LP sleeve.
Please determine the total count of rows and columns in the provided table, respectively. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_220
WTQ_201-csv_26.jpg
How many rows and columns does this table have? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> | Club | Played | Won | Drawn | Lost | Points For | Points Against | Points Difference | Tries For | Tries Against | Try Bonus | Losing Bonus | Points 1 | Saracens (RU) | 22 | 19 | 0 | 3 | 629 | 353 | 276 | 68 | 39 | 10 | 1 | 87 2 | Northampton Saints (CH) | 22 | 16 | 2 | 4 | 604 | 350 | 254 | 72 | 31 | 7 | 3 | 78 3 | Leicester Tigers (SF) | 22 | 15 | 2 | 5 | 542 | 430 | 112 | 59 | 41 | 7 | 3 | 74 4 | Harlequins (SF) | 22 | 15 | 0 | 7 | 437 | 365 | 72 | 43 | 33 | 4 | 3 | 67 5 | Bath | 22 | 14 | 2 | 6 | 495 | 388 | 107 | 48 | 38 | 4 | 3 | 67 6 | Sale Sharks | 22 | 12 | 0 | 10 | 432 | 399 | 33 | 46 | 40 | 3 | 6 | 57 7 | London Wasps | 22 | 9 | 0 | 13 | 451 | 533 | -82 | 48 | 56 | 4 | 9 | 49 8 | Exeter Chiefs | 22 | 9 | 0 | 13 | 426 | 480 | -54 | 40 | 51 | 2 | 7 | 45 9 | Gloucester | 22 | 8 | 0 | 14 | 440 | 539 | -99 | 46 | 60 | 4 | 8 | 44 10 | London Irish | 22 | 7 | 0 | 15 | 396 | 496 | -100 | 40 | 49 | 2 | 6 | 36 11 | Newcastle Falcons | 22 | 3 | 0 | 19 | 281 | 544 | -263 | 23 | 62 | 2 | 8 | 22 12 | Worcester Warriors (R) | 22 | 2 | 0 | 20 | 325 | 581 | -256 | 31 | 64 | 1 | 7 | 16
WTQ_for_TSD
| Club | Played | Won | Drawn | Lost | Points For | Points Against | Points Difference | Tries For | Tries Against | Try Bonus | Losing Bonus | Points 1 | Saracens (RU) | 22 | 19 | 0 | 3 | 629 | 353 | 276 | 68 | 39 | 10 | 1 | 87 2 | Northampton Saints (CH) | 22 | 16 | 2 | 4 | 604 | 350 | 254 | 72 | 31 | 7 | 3 | 78 3 | Leicester Tigers (SF) | 22 | 15 | 2 | 5 | 542 | 430 | 112 | 59 | 41 | 7 | 3 | 74 4 | Harlequins (SF) | 22 | 15 | 0 | 7 | 437 | 365 | 72 | 43 | 33 | 4 | 3 | 67 5 | Bath | 22 | 14 | 2 | 6 | 495 | 388 | 107 | 48 | 38 | 4 | 3 | 67 6 | Sale Sharks | 22 | 12 | 0 | 10 | 432 | 399 | 33 | 46 | 40 | 3 | 6 | 57 7 | London Wasps | 22 | 9 | 0 | 13 | 451 | 533 | -82 | 48 | 56 | 4 | 9 | 49 8 | Exeter Chiefs | 22 | 9 | 0 | 13 | 426 | 480 | -54 | 40 | 51 | 2 | 7 | 45 9 | Gloucester | 22 | 8 | 0 | 14 | 440 | 539 | -99 | 46 | 60 | 4 | 8 | 44 10 | London Irish | 22 | 7 | 0 | 15 | 396 | 496 | -100 | 40 | 49 | 2 | 6 | 36 11 | Newcastle Falcons | 22 | 3 | 0 | 19 | 281 | 544 | -263 | 23 | 62 | 2 | 8 | 22 12 | Worcester Warriors (R) | 22 | 2 | 0 | 20 | 325 | 581 | -256 | 31 | 64 | 1 | 7 | 16
How many rows and columns does this table have? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_221
WTQ_203-csv_335.jpg
How many rows and columns does the given table have? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> Route | Destinations | Via | Frequency (minutes) | Peak Hours Only | Former 1 | Montreal Street St. Lawrence College | Downtown | 30 | | Cataraqui Town Centre-Woods 2 | Kingston Centre Division Street | St. Lawrence College Downtown | 30 | | 3 | Kingston Centre Downtown | Queen Mary Road St. Lawrence College King Street | 30 | | 4 | Princess Street | Cataraqui Town Centre Downtown | 30 | | 6 | Cataraqui Town Centre St. Lawrence College | Gardiners Town Centre | 30 | | Downtown 7 | Dalton/Division Midland/Gardiners | Cataraqui Town Centre Train Station Bus Terminal | 30 | | 9 | Downtown Cataraqui Town Centre | Brock St. / Barrie St. Gardiners Town Centre | 20 | | 10 | Amherstview Cataraqui Town Centre | Collins Bay Road | 30 | | Kingston Centre 11 | Kingston Centre Cataraqui Town Centre | Bath Road Gardiners Town Centre | 30 | | (formerly Route 71) 12 | Kingston Centre Highway 15 | Downtown CFB Kingston (off-peak only) | 30 | | - 12A | CFB Kingston Downtown | | 30 | X | 18 | Train Station Bus Terminal | Downtown Queen's University St. Lawrence College | * | | Student Circuit 19 | Montreal Street Queen's University | Downtown | 30 | X | 14 | Train Station Cataraqui Town Centre / Midland Avenue | Waterloo-Davis Multiplex | 30 | | (formerly Route A) 15 | Reddendale Cataraqui Town Centre - Woods | Gardiners Town Centre | 30 | | (formerly Route B) 16 | Train Station Bus Terminal | Kingston Centre | 30 | | (formerly Route C)
WTQ_for_TSD
Route | Destinations | Via | Frequency (minutes) | Peak Hours Only | Former 1 | Montreal Street St. Lawrence College | Downtown | 30 | | Cataraqui Town Centre-Woods 2 | Kingston Centre Division Street | St. Lawrence College Downtown | 30 | | 3 | Kingston Centre Downtown | Queen Mary Road St. Lawrence College King Street | 30 | | 4 | Princess Street | Cataraqui Town Centre Downtown | 30 | | 6 | Cataraqui Town Centre St. Lawrence College | Gardiners Town Centre | 30 | | Downtown 7 | Dalton/Division Midland/Gardiners | Cataraqui Town Centre Train Station Bus Terminal | 30 | | 9 | Downtown Cataraqui Town Centre | Brock St. / Barrie St. Gardiners Town Centre | 20 | | 10 | Amherstview Cataraqui Town Centre | Collins Bay Road | 30 | | Kingston Centre 11 | Kingston Centre Cataraqui Town Centre | Bath Road Gardiners Town Centre | 30 | | (formerly Route 71) 12 | Kingston Centre Highway 15 | Downtown CFB Kingston (off-peak only) | 30 | | - 12A | CFB Kingston Downtown | | 30 | X | 18 | Train Station Bus Terminal | Downtown Queen's University St. Lawrence College | * | | Student Circuit 19 | Montreal Street Queen's University | Downtown | 30 | X | 14 | Train Station Cataraqui Town Centre / Midland Avenue | Waterloo-Davis Multiplex | 30 | | (formerly Route A) 15 | Reddendale Cataraqui Town Centre - Woods | Gardiners Town Centre | 30 | | (formerly Route B) 16 | Train Station Bus Terminal | Kingston Centre | 30 | | (formerly Route C)
How many rows and columns does the given table have? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_222
WTQ_204-csv_424.jpg
How many rows and columns does this table have? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Season | Series | Team | Races | Wins | Poles | F/Laps | Podiums | Points | Position 2007 | Asian Formula Renault Challenge | Champ Motorsports | 12 | 0 | 0 | 0 | 1 | 64 | 14th 2008 | Asian Formula Renault Challenge | Champ Motorsports | 13 | 0 | 0 | 0 | 3 | 193 | 4th 2009 | Asian Formula Renault Challenge | Asia Racing Team | 12 | 6 | 2 | 4 | 7 | 287 | 2nd 2009 | Formula Renault 2.0 Northern European Cup | Krenek Motorsport | 14 | 0 | 0 | 0 | 0 | 44 | 21st 2010 | ATS Formel 3 Cup | China Sonangol | 5 | 0 | 0 | 0 | 0 | 0 | 19th 2010 | Austria Formula 3 Cup | Sonangol Motopark | 4 | 1 | 2 | 3 | 2 | 35 | 9th 2011 | Formula Pilota China | Asia Racing Team | 12 | 2 | 0 | 0 | 3 | 124 | 2nd 2012 | Formula 3 Euro Series | Angola Racing Team | 21 | 0 | 0 | 0 | 0 | 14 | 14th 2012 | 59th Macau Grand Prix Formula 3 | Angola Racing Team | 2 | 0 | 0 | 0 | 0 | — | 23rd 2012 | Masters of Formula 3 | Angola Racing Team | 1 | 0 | 0 | 0 | 0 | — | 18th 2012 | British Formula 3 Championship | Angola Racing Team | 5 | 0 | 0 | 0 | 0 | — | — 2013 | GP3 Series | Carlin | 16 | 0 | 0 | 0 | 0 | 0 | 23rd
WTQ_for_TSD
Season | Series | Team | Races | Wins | Poles | F/Laps | Podiums | Points | Position 2007 | Asian Formula Renault Challenge | Champ Motorsports | 12 | 0 | 0 | 0 | 1 | 64 | 14th 2008 | Asian Formula Renault Challenge | Champ Motorsports | 13 | 0 | 0 | 0 | 3 | 193 | 4th 2009 | Asian Formula Renault Challenge | Asia Racing Team | 12 | 6 | 2 | 4 | 7 | 287 | 2nd 2009 | Formula Renault 2.0 Northern European Cup | Krenek Motorsport | 14 | 0 | 0 | 0 | 0 | 44 | 21st 2010 | ATS Formel 3 Cup | China Sonangol | 5 | 0 | 0 | 0 | 0 | 0 | 19th 2010 | Austria Formula 3 Cup | Sonangol Motopark | 4 | 1 | 2 | 3 | 2 | 35 | 9th 2011 | Formula Pilota China | Asia Racing Team | 12 | 2 | 0 | 0 | 3 | 124 | 2nd 2012 | Formula 3 Euro Series | Angola Racing Team | 21 | 0 | 0 | 0 | 0 | 14 | 14th 2012 | 59th Macau Grand Prix Formula 3 | Angola Racing Team | 2 | 0 | 0 | 0 | 0 | — | 23rd 2012 | Masters of Formula 3 | Angola Racing Team | 1 | 0 | 0 | 0 | 0 | — | 18th 2012 | British Formula 3 Championship | Angola Racing Team | 5 | 0 | 0 | 0 | 0 | — | — 2013 | GP3 Series | Carlin | 16 | 0 | 0 | 0 | 0 | 0 | 23rd
How many rows and columns does this table have? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_223
WTQ_204-csv_306.jpg
This image shows a table. Tell me the row number and column number of this table. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Rank | Nation | Gold | Silver | Bronze | Total 1 | Netherlands | 8 | 3 | 1 | 12 2 | Australia | 3 | 3 | 4 | 10 3 | United States | 2 | 5 | 1 | 8 4 | Hungary | 1 | 1 | 3 | 5 5 | Canada | 1 | – | 3 | 4 6 | Italy | – | 2 | 1 | 3 7 | Russia | – | 1 | 1 | 2 8 | China | – | – | 1 | 1
WTQ_for_TSD
Rank | Nation | Gold | Silver | Bronze | Total 1 | Netherlands | 8 | 3 | 1 | 12 2 | Australia | 3 | 3 | 4 | 10 3 | United States | 2 | 5 | 1 | 8 4 | Hungary | 1 | 1 | 3 | 5 5 | Canada | 1 | – | 3 | 4 6 | Italy | – | 2 | 1 | 3 7 | Russia | – | 1 | 1 | 2 8 | China | – | – | 1 | 1
This image shows a table. Tell me the row number and column number of this table. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_224
WTQ_202-csv_241.jpg
I need to know the count of rows and columns in this specific table. Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> Title | Year | Peak chart positions US | Peak chart positions US Dance | Peak chart positions US Pop | Peak chart positions US R&B | Peak chart positions GER | Peak chart positions NL | Peak chart positions NOR | Peak chart positions NZ | Peak chart positions SWI | Peak chart positions UK | Album 1980 | \Earth Can Be Just Like Heaven\"" | — | 2 | — | — | — | — | — | — | — | — | 1980 | \I Got the Feeling\"" | — | 2 | — | — | — | — | — | — | — | — | 1980 | \Just Us\"" | — | 2 | — | 29 | — | — | — | — | — | — | 1982 | \It's Raining Men\"" | 46 | 1 | 46 | 34 | 43 | 46 | 8 | 13 | 95 | 2 | 1985 | \No One Can Love You More Than Me\"" | — | 26 | — | — | — | — | — | — | — | — | 1985 | \Well-A-Wiggy\"" | — | — | 107 | 76 | — | — | — | — | — | — | 1993 | \Can You Feel It\"" | — | 2 | — | — | 75 | — | — | — | — | — |
WTQ_for_TSD
Title | Year | Peak chart positions US | Peak chart positions US Dance | Peak chart positions US Pop | Peak chart positions US R&B | Peak chart positions GER | Peak chart positions NL | Peak chart positions NOR | Peak chart positions NZ | Peak chart positions SWI | Peak chart positions UK | Album 1980 | \Earth Can Be Just Like Heaven\"" | — | 2 | — | — | — | — | — | — | — | — | 1980 | \I Got the Feeling\"" | — | 2 | — | — | — | — | — | — | — | — | 1980 | \Just Us\"" | — | 2 | — | 29 | — | — | — | — | — | — | 1982 | \It's Raining Men\"" | 46 | 1 | 46 | 34 | 43 | 46 | 8 | 13 | 95 | 2 | 1985 | \No One Can Love You More Than Me\"" | — | 26 | — | — | — | — | — | — | — | — | 1985 | \Well-A-Wiggy\"" | — | — | 107 | 76 | — | — | — | — | — | — | 1993 | \Can You Feel It\"" | — | 2 | — | — | 75 | — | — | — | — | — |
I need to know the count of rows and columns in this specific table. Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_225
WTQ_204-csv_369.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Golfer | Country | Wins | Match Play | Championship | Invitational | Champions Tiger Woods | United States | 18 | 3: 2003, 2004, 2008 | 7: 1999, 2002, 2003, 2005, 2006, 2007, 2013 | 8: 1999, 2000, 2001, 2005, 2006, 2007, 2009, 2013 | — Geoff Ogilvy | Australia | 3 | 2: 2006, 2009 | 1: 2008 | — | — Darren Clarke | Northern Ireland | 2 | 1: 2000 | — | 1: 2003 | — Ernie Els | South Africa | 2 | — | 2: 2004, 2010 | — | — Hunter Mahan | United States | 2 | 1: 2012 | — | 1: 2010 | — Phil Mickelson | United States | 2 | — | 1: 2009 | — | 1: 2009 Ian Poulter | England | 2 | 1: 2010 | — | — | 1: 2012
WTQ_for_TSD
Golfer | Country | Wins | Match Play | Championship | Invitational | Champions Tiger Woods | United States | 18 | 3: 2003, 2004, 2008 | 7: 1999, 2002, 2003, 2005, 2006, 2007, 2013 | 8: 1999, 2000, 2001, 2005, 2006, 2007, 2009, 2013 | — Geoff Ogilvy | Australia | 3 | 2: 2006, 2009 | 1: 2008 | — | — Darren Clarke | Northern Ireland | 2 | 1: 2000 | — | 1: 2003 | — Ernie Els | South Africa | 2 | — | 2: 2004, 2010 | — | — Hunter Mahan | United States | 2 | 1: 2012 | — | 1: 2010 | — Phil Mickelson | United States | 2 | — | 1: 2009 | — | 1: 2009 Ian Poulter | England | 2 | 1: 2010 | — | — | 1: 2012
For the table shown in this image, can you tell me the row and column numbers of this table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_226
WTQ_204-csv_444.jpg
Please identify the row and column numbers of the table displayed in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Series | Name | Age | Hometown | Occupation | Status BB1 | Craig Phillips | 28 | Liverpool | Builder | 1st - Winner BB1 | Anna Nolan | 29 | Dublin | Office Manager | 2nd - Runner-up BB1 | Darren Ramsay | 23 | London | Millennium Dome Assistant | 3rd - Third place BB1 | Melanie Hill | 26 | London | Computer Sales Woman | 4th - Evicted BB1 | Claire Strutton | 25 | Buckinghamshire | Florist | 5th - Evicted BB1 | Tom McDermott | 28 | County Tyrone | Farmer | 6th - Evicted BB1 | Nichola Holt | 29 | Bolton | Teacher | 7th - Evicted BB1 | Nick Bateman | 32 | Kent | Broker | 8th - Ejected BB1 | Caroline O'Shea | 31 | Birmingham | Marital Aids Seller | 9th - Evicted BB1 | Andrew Davidson | 23 | Hertfordshire | Marketing Product Manager | 10th - Evicted BB1 | Sada Wilkington | 28 | Edinburgh | Writer | 11th - Evicted BB2 | Brian Dowling | 22 | County Kildare | Air Steward | 1st - Winner BB2 | Helen Adams | 22 | South Wales | Hairdresser | 2nd - Runner-up BB2 | Dean O'Loughlin | 37 | Birmingham | Runs own Internet Company | 3rd - Third Place BB2 | Elizabeth Woodcock | 26 | Cumbria | Website Designer | 4th - Evicted BB2 | Paul Clarke | 25 | Reading | CAD designer | 5th - Evicted BB2 | Josh Rafter | 32 | London | Property manager | 6th - Evicted BB2 | Amma Antwi-Agyei | 23 | London | Table Dancer | 7th - Evicted BB2 | Bubble (Paul) Ferguson | 24 | Surrey | Warehouse Operative | 8th - Evicted BB2 | Narinder Kaur | 28 | Leicester | Medical rep | 9th - Evicted BB2 | Stuart Hosking | 36 | Oxford | Director of communications company | 10th - Evicted BB2 | Penny Ellis | 33 | London | Teacher | 11th - Evicted BB3 | Kate Lawler | 22 | London | Technical support administrator | 1st - Winner BB3 | Jonny Regan | 29 | County Durham | Firefighter | 2nd - Runner-up BB3 | Alex Sibley | 23 | London | Model | 3rd - Third Place BB3 | Jade Goody | 20 | London | Dental Nurse | 4th - Evicted BB3 | Tim Culley | 23 | Worcester | Tennis coach | 5th - Evicted BB3 | PJ (Peter) Ellis | 22 | Birmingham | Student | 6th - Evicted BB3 | Adele Roberts | 29 | Southport | PA/DJ | 7th - Evicted BB3 | Sophie Pritchard | 24 | Buckinghamshire | Recruitment Consultant | 8th - Evicted BB3 | Spencer Smith | 22 | Cambridge | Ski Shop Assistant | 9th - Evicted BB3 | Lee Davey | 21 | Leicester | Fitness Instructor | 10th - Evicted BB3 | Sandy Cumming | 43 | London | Personal shopper/Stylist | 11th - Walked BB3 | Alison Hammond | 27 | Birmingham | Cinema Team Leader | 12th - Evicted BB3 | Lynne Moncrieff | 36 | Aberdeen | Student | 13th - Evicted BB3 | Sunita Sharma | 25 | London | Trainee barrister | 14th - Walked BB4 | Cameron Stout | 32 | Orkney | Fish Trader | 1st - Winner BB4 | Ray Shah | 25 | Dublin | IT Systems Administrator | 2nd - Runner-up BB4 | Scott Turner | 27 | Liverpool | Waiter | 3rd - Third Place BB4 | Steph (Stephanie) Coldicott | 28 | Worcester | Visual Merchandiser | 4th - Evicted BB4 | Nush (Annuszka) Nowak | 23 | Worcester | Fine Art Student | 5th - Evicted BB4 | Lisa Jeynes | 35 | South Wales | Shop Manager | 6th - Evicted BB4 | Herjendar \Gos\" Gosal" | 31 | London | Chef | 7th - Evicted BB4 | Tania do Nascimento | 22 | London | Shop Assistant | 8th - Evicted BB4 | Jon Tickle | 29 | Surrey | Unemployed | 9th - Evicted BB4 | Federico Martone | 23 | Glasgow | Waiter | 10th - Evicted BB4 | Sissy (Joanne) Rooney | 26 | Liverpool | Store Assistant | 11th - Evicted BB4 | Justine Sellman | 27 | Leeds | Sales assistant | 12th - Evicted BB4 | Anouska Golebiewski | 20 | Manchester | Nursery Assistant | 13th - Evicted BB5 | Nadia Almada | 27 | London | Store Assistant | 1st - Winner BB5 | Jason Cowan | 30 | South Lanarkshire | Air Steward | 2nd - Runner-up BB5 | Daniel Bryan | 30 | Hull | Hairdresser | 3rd - Third Place BB5 | Shell (Michelle) Jubin | 22 | Glasgow | Student | 4th - Evicted BB5 | Stuart Wilson | 20 | Cheshire | Student | 5th - Evicted BB5 | Michelle Bass | 23 | Newcastle | Mortgage Advisor | 6th - Evicted BB5 | Victor Ebuwa | 23 | London | Singer/Songwriter | 7th - Evicted BB5 | Ahmed Aghil | 44 | Liverpool | Property Developer | 8th - Evicted BB5 | Becki Seddiki | 33 | London | Singer/Songwriter | 9th - Evicted BB5 | Marco Sabba | 21 | Middlesex | Student | 10th - Evicted BB5 | Vanessa Nimmo | 26 | Leeds | Archery Champion | 11th - Evicted BB5 | Emma Greenwood | 20 | Manchester | Administrative Assistant | 12th - Ejected BB5 | Kitten Pinder | 24 | Brighton | Anarchist/Human and Animal rights activist | 13th - Ejected BB6 | Anthony Hutton | 23 | Newcastle | 70s Dancer | 1st - Winner BB6 | Eugene Sully | 27 | Crawley | Student | 2nd - Runner-up BB6 | Makosi Musambasi | 24 | Buckinghamshire | Cardiac Nurse | 3rd - Third Place BB6 | Kinga Karolczak | 20 | London | Market Researcher | 4th - Evicted BB6 | Craig Coates | 20 | Norfolk | Hair Stylist | 5th - Evicted BB6 | Derek Laud | 40 | London | Speech Writer | 6th - Evicted BB6 | Orlaith McAllister | 26 | Belfast | Student/Model | 7th - Walked BB6 | Kemal Shahin | 19 | London | Student/Male Belly dancer | 8th - Evicted BB6 | Science (Kieron) Harvey | 22 | Leeds | Entertainment Entrepreneur | 9th - Evicted BB6 | Vanessa Layton-McIntosh | 19 | London | Student | 10th - Evicted BB6 | Maxwell Ward | 24 | London | Maintenance engineer | 11th - Evicted BB6 | Saskia Howard-Clarke | 23 | London | Promotions Girl | 12th - Evicted BB6 | Roberto Conte | 32 | Liverpool | Teacher | 13th - Evicted BB6 | Sam Heuston | 23 | London | Student | 14th - Evicted BB6 | Lesley Sanderson | 19 | Huddersfield | Sales Assistant | 15th - Evicted BB6 | Mary O'Leary | 30 | Dublin | Psychic advisor/Writer/White witch | 16th - Evicted BB7 | Pete Bennett | 24 | Brighton | Singer | 1st - Winner BB7 | Glyn Wise | 18 | North Wales | Student/Lifeguard | 2nd - Runner-up BB7 | Aisleyne Horgan-Wallace | 27 | London | Model/Promotions Girl | 3rd - Third Place BB7 | Richard Newman | 33 | Northampton | Waiter | 4th - Evicted BB7 | Nikki Grahame | 24 | London | Model/Dancer | 5th - Evicted BB7 | Jennie Corner | 18 | Liverpool | Barmaid/student | 6th - Evicted BB7 | Imogen Thomas | 23 | Llanelli | Bar Hostess | 7th - Evicted BB7 | Susie Verrico | 43 | Kent | Model | 8th - Evicted BB7 | Mikey Dalton | 22 | Liverpool | Software Developer/Model | 9th - Evicted BB7 | Spiral (Glen) Coroner | 22 | Dublin | DJ/Rapper | 10th - Evicted BB7 | Michael Cheshire | 23 | Manchester | Student | 11th - Evicted BB7 | Jayne Kitt | 36 | Berkshire | Recruitment adviser | 12th - Evicted BB7 | Lea Walker | 35 | Nottingham | Porn Star/Model | 13th - Evicted BB7 | Jonathan Leonard | 24 | Cumbria | Doorman | 14th - Evicted BB7 | Lisa Huo | 27 | Manchester | Upholsterer | 15th - Evicted BB7 | Grace Adams-Short | 20 | London | Dance Teacher | 16th - Evicted BB7 | Sam Brodie | 19 | Ayr | Nail Technician | 17th - Evicted BB7 | Sezer Yurtseven | 26 | London | Stock Broker/Property Developer | 18th - Evicted BB7 | George Askew | 19 | London | Student | 19th - Walked BB7 | Bonnie Holt | 19 | Leicester | Care Worker | 20th - Evicted BB7 | Dawn Blake | 38 | Birmingham | Exercise Scientist | 21st - Ejected BB7 | Shahbaz Chauhdry | 37 | Glasgow | Unemployed | 22nd - Walked BB8 | Brian (Olawale) Belo | 19 | Essex | Data Clerk | 1st - Winner BB8 | Amanda Marchant | 18 | Stoke-on-Trent | Student | 2nd - Runner-up BB8 | Sam Marchant | 18 | Stoke-on-Trent | Student | 2nd - Runner-up BB8 | Liam McGough | 22 | County Durham | Tree Surgeon | 3rd - Third Place BB8 | Ziggy (Zac) Lichman | 26 | London | Model | 4th - Evicted BB8 | Carole Vincent | 53 | London | Sexual Health Worker | 5th - Evicted BB8 | Jonty Stern | 36 | London | Museum assistant | 6th - Evicted BB8 | Kara-Louise Horne | 22 | London | Student | 7th - Evicted BB8 | Tracey Barnard | 36 | Cambridge | Cleaner | 8th - Evicted BB8 | Gerasimos Stergiopoulos | 31 | London | Gallery Researcher | 9th - Evicted BB8 | Amy Alexandra | 21 | Grimsby | Glamour Model | 10th - Evicted BB8 | David Parnaby | 25 | Ayr | Visual Manager | 11th - Evicted BB8 | Shanessa Reilly | 26 | Cardiff | Care Assistant/Stripper | 12th - Evicted BB8 | Chanelle Hayes | 19 | Yorkshire | Student | 13th - Walked BB8 | Charley Uchea | 21 | London | Unemployed | 14th - Evicted BB8 | Nicky Maxwell | 27 | Hertfordshire | Bank Worker | 15th - Evicted BB8 | Laura Williams | 23 | South Wales | Nanny | 16th - Evicted BB8 | Jonathan Durden | 49 | London | Entrepreneur | 17th - Walked BB8 | Billi Bhatti | 25 | London | Model | 18th - Evicted BB8 | Seány O'Kane | 25 | Derry | Charity Worker | 19th - Evicted BB8 | Shabnam Paryani | 22 | London | Receptionist | 20th - Evicted BB8 | Lesley Brain | 60 | Gloucestershire | Retired | 21st - Walked BB8 | Emily Parr | 19 | Bristol | Student | 22nd - Ejected BB9 | Rachel Rice | 24 | Torfaen | Trainee Teacher/Actress | 1st - Winner BB9 | Mikey (Michael) Hughes | 33 | Glasgow | Radio Producer | 2nd - Runner-up BB9 | Sara Folino | 27 | London | Personal Assistant | 3rd - Third Place BB9 | Rex Newmark | 24 | London | Chef | 4th - Evicted BB9 | Darnell Swallow | 26 | Suffolk | Songwriter | 5th - Evicted BB9 | Kathreya Kasisopa | 30 | Kent | Massage Therapist | 6th - Evicted BB9 | Mohamed Mohamed | 23 | London | Toy Demonstrator | 7th - Evicted BB9 | Lisa Appleton | 40 | Cheshire | Beauty and Tanning Sales Rep | 8th - Evicted BB9 | Nicole Cammack | 19 | Surrey | Student | 9th - Evicted BB9 | Stuart Pilkington | 25 | Manchester | Personal Trainer/Property Developer | 10th - Evicted BB9 | Dale Howard | 21 | Liverpool | Student/Part time DJ | 11th - Evicted BB9 | Luke Marsden | 20 | Bolton | Student | 12th - Evicted BB9 | Maysoon Shaladi | 28 | Hertfordshire | Model | 13th - Walked BB9 | Rebecca Shiner | 21 | Coventry | Nursery Nurse | 14th - Evicted BB9 | Belinda Harris-Reid | 44 | Exeter | Theatre Director | 15th - Evicted BB9 | Mario Marconi (Shaun Astbury) | 43 | Cheshire | Civil Servant | 16th - Evicted BB9 | Jennifer Clark | 22 | County Durham | Model | 17th - Evicted BB9 | Sylvia Barrie | 21 | London | Student | 18th - Evicted BB9 | Dennis McHugh | 23 | Edinburgh | Dance Teacher | 19th - Ejected BB9 | Alexandra De-Gale | 23 | Surrey | Accounts Clerk | 20th - Ejected BB9 | Stephanie McMichael | 19 | Liverpool | Student | 21st - Evicted BB10 | Sophie (Dogface) Reade | 20 | Cheshire | Model | 1st - Winner BB10 | Siavash Sabbaghpour | 23 | London | Event Organiser/Stylist/Model | 2nd - Runner-up BB10 | David Ramsden | 28 | Yorkshire | Clothing Recycler | 3rd - Third Place BB10 | Charlie Drummond | 22 | Newcastle | Jobcentre Advisor | 4th - Evicted BB10 | Rodrigo Lopes | 23 | Manchester | Student | 5th - Evicted BB10 | Lisa Wallace | 41 | Birmingham | Unemployed | 6th - Evicted BB10 | Marcus Akin | 35 | London | Carpenter/Glazier | 7th - Evicted BB10 | Bea Hamill | 24 | Bristol | Recruitment Consultant | 8th - Evicted BB10 | Freddie (Halfwit) Fisher | 23 | Shropshire | Web Programmer | 9th - Evicted BB10 | Hira Habibshah | 25 | Dublin | Fashion Designer | 10th - Evicted BB10 | Isaac Stout | 23 | Ohio, USA | Bar Manager | 11th - Walked BB10 | Noirin Kelly | 25 | Dublin | Retail Manager | 12th - Evicted BB10 | Tom Oliver | 27 | Northampton | Yacht Importer | 13th - Walked BB10 | Kenneth Tong | 24 | Edinburgh | Self Employed | 14th - Walked BB10 | Karly Ashworth | 21 | Fife | Unemployed/Model | 15th - Evicted BB10 | Kris Donnelly | 24 | Manchester | Visual Merchandiser | 16th - Evicted BB10 | Sree Desari | 25 | Hertfordshire | Student Union President | 17th - Evicted BB10 | Angel McKenzie | 35 | London | Professional Boxer | 18th - Evicted BB10 | Cairon Austin-Hill | 18 | London | Student | 19th - Evicted BB10 | Sophia Brown | 26 | London | Private Banking Assistant | 20th - Evicted BB10 | Saffia Corden | 27 | Nottingham | Dental Nurse | 21st - Walked BB10 | Beinazir Lasharie | 28 | London | Receptionist | 22nd - Evicted BB11 | Josie Gibson | 25 | Bristol | Financial sales rep | 1st - Winner BB11 | Dave (David) Vaughan | 39 | Torfaen | Minister | 2nd - Runner-up BB11 | Mario Mugan | 28 | Essex | Unemployed | 3rd - Third Place BB11 | JJ (Joe-John Daniel) Bird | 23 | London | Professional boxer/barman | 4th - Evicted BB11 | Andrew Edmonds | 19 | Dorset | Student | 5th - Evicted BB11 | John James Parton | 24 | Melbourne, Australia | Vehicle bodybuilder | 6th - Evicted BB11 | Sam (Samuel) Pepper | 21 | Kent | Graffiti artist | 7th - Evicted BB11 | Corin Forshaw | 29 | Manchester | Retail worker | 8th - Evicted BB11 | Steve (Steven) Gill | 40 | Leicester | Unemployed | 9th - Evicted BB11 | Jo Butler | 41 | Luton | Makeup artist | 10th - Evicted BB11 | Rachel Ifon | 28 | Liverpool | Flight Attendant | 11th - Evicted BB11 | Ben (Benjamin) Duncan | 30 | London | Writer and broadcaster | 12th - Evicted BB11 | Laura McAdam | 20 | Warwickshire | Sales assistant | 13th - Walked BB11 | Keeley Johnson | 30 | Manchester | Travel Agency Manager | 14th - Injury BB11 | Caoimhe Guilfoyle | 22 | Dublin | DJ | 15th - Walked BB11 | Ife Kuku | 25 | Milton Keynes | Dancer | 16th - Evicted BB11 | Nathan Dunn | 25 | Bradford | Joiner | 17th - Evicted BB11 | Shabby (Keeley) Katchadourian | 24 | London | Film maker | 18th - Walked BB11 | Sunshine (Yvette) Martyn | 24 | Peterborough | Medical student | 19th - Evicted BB11 | Govan Hinds | 21 | Leicester | Voluntary worker | 20th - Evicted BB11 | Rachael White | 25 | Nottingham | Hair stylist | 21st - Evicted BB12 | Aaron Allard-Morgan | 30 | Weston-super-Mare | Contract manager | 1st - Winner BB12 | Jay McKray | 27 | Newcastle | Plumber/Fitness Instructor/DJ/barber | 2nd - Runner-up BB12 | Alex Lee | 18 | Newcastle | Crew Member at McDonalds | 3rd - Third Place BB12 | Louise Cliffe | 25 | Manchester | Model/Actress | 4th - Evicted BB12 | Tom O'Connell | 20 | Birmingham | Sales Assistant | 5th - Evicted BB12 | Faye Palmer | 20 | Tamworth | Professional Wrestler | 6th - Evicted BB12 | Harry Blake | 23 | Cheshire | Marketing Director/Business Investor | 7th - Evicted BB12 | Jem Palmer | 28 | Tamworth | Professional Wrestler | 8th - Walked BB12 | Anton Murphy | 23 | London | Musician | 9th - Evicted BB12 | Aden Theobald | 19 | London | Student | 10th - Evicted BB12 | Maisy James | 19 | Kent | Store Assistant | 11th - Evicted BB12 | Mark Henderson | 28 | London | Sales | 12th - Walked BB12 | Heaven Afrika | 30 | London | Model/Holistic Healer | 13th - Evicted BB12 | Rebeckah Vaughan | 28 | Wirral | Hostess/Entrepreneur | 14th - Evicted BB12 | Tashie Jackson | 21 | Oxford | Singer & Actress | 15th - Evicted BB13 | Luke Anderson | 31 | North Wales | Development chef | 1st - Winner BB13 | Adam Kelly | 27 | Dudley | Unemployed | 2nd - Runner-up BB13 | Deana Uppal | 23 | Sandwell | Model | 3rd - Third Place BB13 | Sara McLean | 22 | Edinburgh | Student/Model | 4th - Evicted BB13 | Luke Scrase | 24 | Stoke-on-Trent | Nightclub promoter | 5th - Evicted BB13 | Ashleigh Hughes | 20 | Essex | Retail Sales Supervisor | 6th - Evicted BB13 | Scott Mason | 21 | Cheshire | Student | 7th - Evicted BB13 | Conor McIntyre | 24 | Derry | Personal Trainer | 8th - Walked BB13 | Becky Hannon | 19 | Blackburn | Student | 9th - Evicted BB13 | Caroline Wharram | 20 | London | Unemployed | 10th - Evicted BB13 | Lauren Carre | 20 | Jersey | Student | 11th - Evicted BB13 | Shievonne Robinson | 28 | London | Shop Assistant Manager | 12th - Evicted BB13 | Arron Lowe | 23 | Manchester | Model | 13th - Evicted BB13 | Lydia Louisa | 25 | Cheshire | Dancer | 14th - Evicted BB13 | Benedict Garrett | 32 | Manchester | Stripper/Porn Star | 15th - Evicted BB13 | Chris James | 21 | Luton | Doorman | 16th - Evicted BB13 | Victoria Eisermann | 41 | Reading | Model/Animal Rights Campaigner | 17th - Evicted BB14 | Sam Evans | 23 | Llanelli | Stockroom Assistant | 1st - Winner BB14 | Dexter Koh | 28 | London | Celebrity publicist | 2nd - Runner-up BB14 | Gina Rio | 24 | London | Socialite | 3rd - Third Place BB14 | Jack and Joe Glenny | 18 | Hertfordshire | Supermarket checkout assistants | 4th - Evicted BB14 | Charlie Travers | 26 | Hertfordshire | Receptionist | 5th - Evicted BB14 | Sophie Lawrence | 20 | London | Dental Nurse | 6th - Evicted BB14 | Hazel O'Sullivan | 24 | Dublin | Glamour Model | 7th - Evicted BB14 | Callum Knell | 28 | Kent | Sports coach | 8th - Evicted BB14 | Dan Neal | 33 | London | Unemployed | 9th - Evicted BB14 | Jackie Travers | 59 | Hertfordshire | Dance Instructor | 10th - Evicted BB14 | Daley Ojuederie | 28 | London | Professional Boxer | 11th - Ejected BB14 | Wolfy Millington | 20 | Bolton | Student | 12th - Evicted BB14 | Jemima Slade | 41 | London | Dating website owner | 13th - Evicted BB14 | Sallie Axl | 26 | Wirral | Glamour Model | 14th - Evicted TBB | Paul Brennan | 18 | Belfast | Student | 1st - Winner TBB | Caroline Cloke | 18 | Kent | Student | 2nd - Runner-up TBB | Tracey Fowler | 18 | Cheshire | Student | 3rd - Third Place TBB | Tommy Wright | 18 | Dorset | Student | 4th - Evicted TBB | Jade Dyer | 18 | Suffolk | Student | 5th - Evicted TBB | James Kelly | 18 | Glasgow | Student | 6th - Ejected TBB | Shaneen Dawkins | 18 | Leeds | Student | 7th - Evicted TBB | Hasan Shah | 18 | London | Student | 8th - Evicted BB:CH | John Loughton | 20 | Edinburgh | Politician | 1st - Winner BB:CH | Emilia Arata | 18 | Birmingham | Circus Performer | 2nd - Runner-up BB:CH | Amy Jackson | 21 | Oxford | Conceptual Artist | 3rd - Third Place BB:CH | Anthony Ogogo | 19 | Suffolk | Boxer | 4th - Evicted BB:CH | Jeremy Metcalfe | 19 | Hampshire | Racing Driver | 5th - Evicted BB:CH | Nathan Fagan-Gayle | 21 | London | Singer/Songwriter | 6th - Evicted BB:CH | Calista Robertson | 19 | London | Classical Musician | 7th - Evicted BB:CH | Jay Wilson | 19 | London | Fashion Designer | 8th - Evicted BB:CH | Latoya Satnarine | 19 | London | Dancer | 9th - Evicted BB:CH | Victor Arata | 19 | Birmingham | Circus Performer | 10th - Evicted BB:CH | Liam Young | 19 | Liverpool | Entrepreneur | 11th - Evicted BB:CH | Jade Eden | 21 | London | Beauty Queen | 12th - Evicted BBP | Anouska Golebiewski | 22 | Manchester | Participated in BB4 | Not competing BBP | Jade Goody | 23 | London | Participated in BB3 | Not competing BBP | Kitten Pinder | 25 | Brighton | Participated in BB5 | Not competing BBP | Marco Sabba | 21 | Middlesex | Participated in BB5 | Not competing BBP | Mel (Melanie) Hill | 30 | London | Participated in BB1 | Not competing BBP | Narinder Kaur | 23 | Leicester | Participated in BB2 | Not competing BBP | Nick Bateman | 37 | Kent | Participated in BB1 | Not competing BBP | Spencer Smith | 25 | Cambridge | Participated in BB3 | Not competing BBP | Tim Culley | 22 | Worcester | Participated in BB3 | Not competing BBP | Victor Ebuwa | 23 | London | Participated in BB5 | Not competing UBB | Brian Dowling | 32 | County Kildare | Participated in BB2 | 1st - Winner UBB | Nikki Grahame | 28 | London | Participated in BB7 | 2nd - Runner-up UBB | Chantelle Houghton | 27 | Essex | Participated in CBB5 | 3rd - Third Place UBB | Victor Ebuwa | 29 | London | Participated in BB5 | 4th - Evicted UBB | Nick Bateman | 42 | Kent | Participated in BB1 | 5th - Evicted UBB | Preston | 28 | Brighton | Participated in CBB4 | 6th - Evicted UBB | Ulrika Jonsson | 43 | Buckinghamshire | Participated in CBB6 | 7th - Evicted UBB | Vanessa Feltz | 48 | London | Participated in CBB1 | 8th - Evicted UBB | Michelle Bass | 29 | Newcastle | Participated in BB5 | 9th - Evicted UBB | Nadia Almada | 33 | London | Participated in BB5 | 10th - Evicted UBB | Makosi Musambasi | 29 | Buckinghamshire | Participated in BB6 | 11th - Evicted UBB | Coolio | 47 | Pennsylvania, USA | Participated in CBB6 | 12th - Ejected UBB | John McCririck | 70 | London | Participated in CBB3 | 13th - Evicted UBB | Josie Gibson | 25 | Bristol | Participated in BB11 | 14th - Walked
WTQ_for_TSD
Series | Name | Age | Hometown | Occupation | Status BB1 | Craig Phillips | 28 | Liverpool | Builder | 1st - Winner BB1 | Anna Nolan | 29 | Dublin | Office Manager | 2nd - Runner-up BB1 | Darren Ramsay | 23 | London | Millennium Dome Assistant | 3rd - Third place BB1 | Melanie Hill | 26 | London | Computer Sales Woman | 4th - Evicted BB1 | Claire Strutton | 25 | Buckinghamshire | Florist | 5th - Evicted BB1 | Tom McDermott | 28 | County Tyrone | Farmer | 6th - Evicted BB1 | Nichola Holt | 29 | Bolton | Teacher | 7th - Evicted BB1 | Nick Bateman | 32 | Kent | Broker | 8th - Ejected BB1 | Caroline O'Shea | 31 | Birmingham | Marital Aids Seller | 9th - Evicted BB1 | Andrew Davidson | 23 | Hertfordshire | Marketing Product Manager | 10th - Evicted BB1 | Sada Wilkington | 28 | Edinburgh | Writer | 11th - Evicted BB2 | Brian Dowling | 22 | County Kildare | Air Steward | 1st - Winner BB2 | Helen Adams | 22 | South Wales | Hairdresser | 2nd - Runner-up BB2 | Dean O'Loughlin | 37 | Birmingham | Runs own Internet Company | 3rd - Third Place BB2 | Elizabeth Woodcock | 26 | Cumbria | Website Designer | 4th - Evicted BB2 | Paul Clarke | 25 | Reading | CAD designer | 5th - Evicted BB2 | Josh Rafter | 32 | London | Property manager | 6th - Evicted BB2 | Amma Antwi-Agyei | 23 | London | Table Dancer | 7th - Evicted BB2 | Bubble (Paul) Ferguson | 24 | Surrey | Warehouse Operative | 8th - Evicted BB2 | Narinder Kaur | 28 | Leicester | Medical rep | 9th - Evicted BB2 | Stuart Hosking | 36 | Oxford | Director of communications company | 10th - Evicted BB2 | Penny Ellis | 33 | London | Teacher | 11th - Evicted BB3 | Kate Lawler | 22 | London | Technical support administrator | 1st - Winner BB3 | Jonny Regan | 29 | County Durham | Firefighter | 2nd - Runner-up BB3 | Alex Sibley | 23 | London | Model | 3rd - Third Place BB3 | Jade Goody | 20 | London | Dental Nurse | 4th - Evicted BB3 | Tim Culley | 23 | Worcester | Tennis coach | 5th - Evicted BB3 | PJ (Peter) Ellis | 22 | Birmingham | Student | 6th - Evicted BB3 | Adele Roberts | 29 | Southport | PA/DJ | 7th - Evicted BB3 | Sophie Pritchard | 24 | Buckinghamshire | Recruitment Consultant | 8th - Evicted BB3 | Spencer Smith | 22 | Cambridge | Ski Shop Assistant | 9th - Evicted BB3 | Lee Davey | 21 | Leicester | Fitness Instructor | 10th - Evicted BB3 | Sandy Cumming | 43 | London | Personal shopper/Stylist | 11th - Walked BB3 | Alison Hammond | 27 | Birmingham | Cinema Team Leader | 12th - Evicted BB3 | Lynne Moncrieff | 36 | Aberdeen | Student | 13th - Evicted BB3 | Sunita Sharma | 25 | London | Trainee barrister | 14th - Walked BB4 | Cameron Stout | 32 | Orkney | Fish Trader | 1st - Winner BB4 | Ray Shah | 25 | Dublin | IT Systems Administrator | 2nd - Runner-up BB4 | Scott Turner | 27 | Liverpool | Waiter | 3rd - Third Place BB4 | Steph (Stephanie) Coldicott | 28 | Worcester | Visual Merchandiser | 4th - Evicted BB4 | Nush (Annuszka) Nowak | 23 | Worcester | Fine Art Student | 5th - Evicted BB4 | Lisa Jeynes | 35 | South Wales | Shop Manager | 6th - Evicted BB4 | Herjendar \Gos\" Gosal" | 31 | London | Chef | 7th - Evicted BB4 | Tania do Nascimento | 22 | London | Shop Assistant | 8th - Evicted BB4 | Jon Tickle | 29 | Surrey | Unemployed | 9th - Evicted BB4 | Federico Martone | 23 | Glasgow | Waiter | 10th - Evicted BB4 | Sissy (Joanne) Rooney | 26 | Liverpool | Store Assistant | 11th - Evicted BB4 | Justine Sellman | 27 | Leeds | Sales assistant | 12th - Evicted BB4 | Anouska Golebiewski | 20 | Manchester | Nursery Assistant | 13th - Evicted BB5 | Nadia Almada | 27 | London | Store Assistant | 1st - Winner BB5 | Jason Cowan | 30 | South Lanarkshire | Air Steward | 2nd - Runner-up BB5 | Daniel Bryan | 30 | Hull | Hairdresser | 3rd - Third Place BB5 | Shell (Michelle) Jubin | 22 | Glasgow | Student | 4th - Evicted BB5 | Stuart Wilson | 20 | Cheshire | Student | 5th - Evicted BB5 | Michelle Bass | 23 | Newcastle | Mortgage Advisor | 6th - Evicted BB5 | Victor Ebuwa | 23 | London | Singer/Songwriter | 7th - Evicted BB5 | Ahmed Aghil | 44 | Liverpool | Property Developer | 8th - Evicted BB5 | Becki Seddiki | 33 | London | Singer/Songwriter | 9th - Evicted BB5 | Marco Sabba | 21 | Middlesex | Student | 10th - Evicted BB5 | Vanessa Nimmo | 26 | Leeds | Archery Champion | 11th - Evicted BB5 | Emma Greenwood | 20 | Manchester | Administrative Assistant | 12th - Ejected BB5 | Kitten Pinder | 24 | Brighton | Anarchist/Human and Animal rights activist | 13th - Ejected BB6 | Anthony Hutton | 23 | Newcastle | 70s Dancer | 1st - Winner BB6 | Eugene Sully | 27 | Crawley | Student | 2nd - Runner-up BB6 | Makosi Musambasi | 24 | Buckinghamshire | Cardiac Nurse | 3rd - Third Place BB6 | Kinga Karolczak | 20 | London | Market Researcher | 4th - Evicted BB6 | Craig Coates | 20 | Norfolk | Hair Stylist | 5th - Evicted BB6 | Derek Laud | 40 | London | Speech Writer | 6th - Evicted BB6 | Orlaith McAllister | 26 | Belfast | Student/Model | 7th - Walked BB6 | Kemal Shahin | 19 | London | Student/Male Belly dancer | 8th - Evicted BB6 | Science (Kieron) Harvey | 22 | Leeds | Entertainment Entrepreneur | 9th - Evicted BB6 | Vanessa Layton-McIntosh | 19 | London | Student | 10th - Evicted BB6 | Maxwell Ward | 24 | London | Maintenance engineer | 11th - Evicted BB6 | Saskia Howard-Clarke | 23 | London | Promotions Girl | 12th - Evicted BB6 | Roberto Conte | 32 | Liverpool | Teacher | 13th - Evicted BB6 | Sam Heuston | 23 | London | Student | 14th - Evicted BB6 | Lesley Sanderson | 19 | Huddersfield | Sales Assistant | 15th - Evicted BB6 | Mary O'Leary | 30 | Dublin | Psychic advisor/Writer/White witch | 16th - Evicted BB7 | Pete Bennett | 24 | Brighton | Singer | 1st - Winner BB7 | Glyn Wise | 18 | North Wales | Student/Lifeguard | 2nd - Runner-up BB7 | Aisleyne Horgan-Wallace | 27 | London | Model/Promotions Girl | 3rd - Third Place BB7 | Richard Newman | 33 | Northampton | Waiter | 4th - Evicted BB7 | Nikki Grahame | 24 | London | Model/Dancer | 5th - Evicted BB7 | Jennie Corner | 18 | Liverpool | Barmaid/student | 6th - Evicted BB7 | Imogen Thomas | 23 | Llanelli | Bar Hostess | 7th - Evicted BB7 | Susie Verrico | 43 | Kent | Model | 8th - Evicted BB7 | Mikey Dalton | 22 | Liverpool | Software Developer/Model | 9th - Evicted BB7 | Spiral (Glen) Coroner | 22 | Dublin | DJ/Rapper | 10th - Evicted BB7 | Michael Cheshire | 23 | Manchester | Student | 11th - Evicted BB7 | Jayne Kitt | 36 | Berkshire | Recruitment adviser | 12th - Evicted BB7 | Lea Walker | 35 | Nottingham | Porn Star/Model | 13th - Evicted BB7 | Jonathan Leonard | 24 | Cumbria | Doorman | 14th - Evicted BB7 | Lisa Huo | 27 | Manchester | Upholsterer | 15th - Evicted BB7 | Grace Adams-Short | 20 | London | Dance Teacher | 16th - Evicted BB7 | Sam Brodie | 19 | Ayr | Nail Technician | 17th - Evicted BB7 | Sezer Yurtseven | 26 | London | Stock Broker/Property Developer | 18th - Evicted BB7 | George Askew | 19 | London | Student | 19th - Walked BB7 | Bonnie Holt | 19 | Leicester | Care Worker | 20th - Evicted BB7 | Dawn Blake | 38 | Birmingham | Exercise Scientist | 21st - Ejected BB7 | Shahbaz Chauhdry | 37 | Glasgow | Unemployed | 22nd - Walked BB8 | Brian (Olawale) Belo | 19 | Essex | Data Clerk | 1st - Winner BB8 | Amanda Marchant | 18 | Stoke-on-Trent | Student | 2nd - Runner-up BB8 | Sam Marchant | 18 | Stoke-on-Trent | Student | 2nd - Runner-up BB8 | Liam McGough | 22 | County Durham | Tree Surgeon | 3rd - Third Place BB8 | Ziggy (Zac) Lichman | 26 | London | Model | 4th - Evicted BB8 | Carole Vincent | 53 | London | Sexual Health Worker | 5th - Evicted BB8 | Jonty Stern | 36 | London | Museum assistant | 6th - Evicted BB8 | Kara-Louise Horne | 22 | London | Student | 7th - Evicted BB8 | Tracey Barnard | 36 | Cambridge | Cleaner | 8th - Evicted BB8 | Gerasimos Stergiopoulos | 31 | London | Gallery Researcher | 9th - Evicted BB8 | Amy Alexandra | 21 | Grimsby | Glamour Model | 10th - Evicted BB8 | David Parnaby | 25 | Ayr | Visual Manager | 11th - Evicted BB8 | Shanessa Reilly | 26 | Cardiff | Care Assistant/Stripper | 12th - Evicted BB8 | Chanelle Hayes | 19 | Yorkshire | Student | 13th - Walked BB8 | Charley Uchea | 21 | London | Unemployed | 14th - Evicted BB8 | Nicky Maxwell | 27 | Hertfordshire | Bank Worker | 15th - Evicted BB8 | Laura Williams | 23 | South Wales | Nanny | 16th - Evicted BB8 | Jonathan Durden | 49 | London | Entrepreneur | 17th - Walked BB8 | Billi Bhatti | 25 | London | Model | 18th - Evicted BB8 | Seány O'Kane | 25 | Derry | Charity Worker | 19th - Evicted BB8 | Shabnam Paryani | 22 | London | Receptionist | 20th - Evicted BB8 | Lesley Brain | 60 | Gloucestershire | Retired | 21st - Walked BB8 | Emily Parr | 19 | Bristol | Student | 22nd - Ejected BB9 | Rachel Rice | 24 | Torfaen | Trainee Teacher/Actress | 1st - Winner BB9 | Mikey (Michael) Hughes | 33 | Glasgow | Radio Producer | 2nd - Runner-up BB9 | Sara Folino | 27 | London | Personal Assistant | 3rd - Third Place BB9 | Rex Newmark | 24 | London | Chef | 4th - Evicted BB9 | Darnell Swallow | 26 | Suffolk | Songwriter | 5th - Evicted BB9 | Kathreya Kasisopa | 30 | Kent | Massage Therapist | 6th - Evicted BB9 | Mohamed Mohamed | 23 | London | Toy Demonstrator | 7th - Evicted BB9 | Lisa Appleton | 40 | Cheshire | Beauty and Tanning Sales Rep | 8th - Evicted BB9 | Nicole Cammack | 19 | Surrey | Student | 9th - Evicted BB9 | Stuart Pilkington | 25 | Manchester | Personal Trainer/Property Developer | 10th - Evicted BB9 | Dale Howard | 21 | Liverpool | Student/Part time DJ | 11th - Evicted BB9 | Luke Marsden | 20 | Bolton | Student | 12th - Evicted BB9 | Maysoon Shaladi | 28 | Hertfordshire | Model | 13th - Walked BB9 | Rebecca Shiner | 21 | Coventry | Nursery Nurse | 14th - Evicted BB9 | Belinda Harris-Reid | 44 | Exeter | Theatre Director | 15th - Evicted BB9 | Mario Marconi (Shaun Astbury) | 43 | Cheshire | Civil Servant | 16th - Evicted BB9 | Jennifer Clark | 22 | County Durham | Model | 17th - Evicted BB9 | Sylvia Barrie | 21 | London | Student | 18th - Evicted BB9 | Dennis McHugh | 23 | Edinburgh | Dance Teacher | 19th - Ejected BB9 | Alexandra De-Gale | 23 | Surrey | Accounts Clerk | 20th - Ejected BB9 | Stephanie McMichael | 19 | Liverpool | Student | 21st - Evicted BB10 | Sophie (Dogface) Reade | 20 | Cheshire | Model | 1st - Winner BB10 | Siavash Sabbaghpour | 23 | London | Event Organiser/Stylist/Model | 2nd - Runner-up BB10 | David Ramsden | 28 | Yorkshire | Clothing Recycler | 3rd - Third Place BB10 | Charlie Drummond | 22 | Newcastle | Jobcentre Advisor | 4th - Evicted BB10 | Rodrigo Lopes | 23 | Manchester | Student | 5th - Evicted BB10 | Lisa Wallace | 41 | Birmingham | Unemployed | 6th - Evicted BB10 | Marcus Akin | 35 | London | Carpenter/Glazier | 7th - Evicted BB10 | Bea Hamill | 24 | Bristol | Recruitment Consultant | 8th - Evicted BB10 | Freddie (Halfwit) Fisher | 23 | Shropshire | Web Programmer | 9th - Evicted BB10 | Hira Habibshah | 25 | Dublin | Fashion Designer | 10th - Evicted BB10 | Isaac Stout | 23 | Ohio, USA | Bar Manager | 11th - Walked BB10 | Noirin Kelly | 25 | Dublin | Retail Manager | 12th - Evicted BB10 | Tom Oliver | 27 | Northampton | Yacht Importer | 13th - Walked BB10 | Kenneth Tong | 24 | Edinburgh | Self Employed | 14th - Walked BB10 | Karly Ashworth | 21 | Fife | Unemployed/Model | 15th - Evicted BB10 | Kris Donnelly | 24 | Manchester | Visual Merchandiser | 16th - Evicted BB10 | Sree Desari | 25 | Hertfordshire | Student Union President | 17th - Evicted BB10 | Angel McKenzie | 35 | London | Professional Boxer | 18th - Evicted BB10 | Cairon Austin-Hill | 18 | London | Student | 19th - Evicted BB10 | Sophia Brown | 26 | London | Private Banking Assistant | 20th - Evicted BB10 | Saffia Corden | 27 | Nottingham | Dental Nurse | 21st - Walked BB10 | Beinazir Lasharie | 28 | London | Receptionist | 22nd - Evicted BB11 | Josie Gibson | 25 | Bristol | Financial sales rep | 1st - Winner BB11 | Dave (David) Vaughan | 39 | Torfaen | Minister | 2nd - Runner-up BB11 | Mario Mugan | 28 | Essex | Unemployed | 3rd - Third Place BB11 | JJ (Joe-John Daniel) Bird | 23 | London | Professional boxer/barman | 4th - Evicted BB11 | Andrew Edmonds | 19 | Dorset | Student | 5th - Evicted BB11 | John James Parton | 24 | Melbourne, Australia | Vehicle bodybuilder | 6th - Evicted BB11 | Sam (Samuel) Pepper | 21 | Kent | Graffiti artist | 7th - Evicted BB11 | Corin Forshaw | 29 | Manchester | Retail worker | 8th - Evicted BB11 | Steve (Steven) Gill | 40 | Leicester | Unemployed | 9th - Evicted BB11 | Jo Butler | 41 | Luton | Makeup artist | 10th - Evicted BB11 | Rachel Ifon | 28 | Liverpool | Flight Attendant | 11th - Evicted BB11 | Ben (Benjamin) Duncan | 30 | London | Writer and broadcaster | 12th - Evicted BB11 | Laura McAdam | 20 | Warwickshire | Sales assistant | 13th - Walked BB11 | Keeley Johnson | 30 | Manchester | Travel Agency Manager | 14th - Injury BB11 | Caoimhe Guilfoyle | 22 | Dublin | DJ | 15th - Walked BB11 | Ife Kuku | 25 | Milton Keynes | Dancer | 16th - Evicted BB11 | Nathan Dunn | 25 | Bradford | Joiner | 17th - Evicted BB11 | Shabby (Keeley) Katchadourian | 24 | London | Film maker | 18th - Walked BB11 | Sunshine (Yvette) Martyn | 24 | Peterborough | Medical student | 19th - Evicted BB11 | Govan Hinds | 21 | Leicester | Voluntary worker | 20th - Evicted BB11 | Rachael White | 25 | Nottingham | Hair stylist | 21st - Evicted BB12 | Aaron Allard-Morgan | 30 | Weston-super-Mare | Contract manager | 1st - Winner BB12 | Jay McKray | 27 | Newcastle | Plumber/Fitness Instructor/DJ/barber | 2nd - Runner-up BB12 | Alex Lee | 18 | Newcastle | Crew Member at McDonalds | 3rd - Third Place BB12 | Louise Cliffe | 25 | Manchester | Model/Actress | 4th - Evicted BB12 | Tom O'Connell | 20 | Birmingham | Sales Assistant | 5th - Evicted BB12 | Faye Palmer | 20 | Tamworth | Professional Wrestler | 6th - Evicted BB12 | Harry Blake | 23 | Cheshire | Marketing Director/Business Investor | 7th - Evicted BB12 | Jem Palmer | 28 | Tamworth | Professional Wrestler | 8th - Walked BB12 | Anton Murphy | 23 | London | Musician | 9th - Evicted BB12 | Aden Theobald | 19 | London | Student | 10th - Evicted BB12 | Maisy James | 19 | Kent | Store Assistant | 11th - Evicted BB12 | Mark Henderson | 28 | London | Sales | 12th - Walked BB12 | Heaven Afrika | 30 | London | Model/Holistic Healer | 13th - Evicted BB12 | Rebeckah Vaughan | 28 | Wirral | Hostess/Entrepreneur | 14th - Evicted BB12 | Tashie Jackson | 21 | Oxford | Singer & Actress | 15th - Evicted BB13 | Luke Anderson | 31 | North Wales | Development chef | 1st - Winner BB13 | Adam Kelly | 27 | Dudley | Unemployed | 2nd - Runner-up BB13 | Deana Uppal | 23 | Sandwell | Model | 3rd - Third Place BB13 | Sara McLean | 22 | Edinburgh | Student/Model | 4th - Evicted BB13 | Luke Scrase | 24 | Stoke-on-Trent | Nightclub promoter | 5th - Evicted BB13 | Ashleigh Hughes | 20 | Essex | Retail Sales Supervisor | 6th - Evicted BB13 | Scott Mason | 21 | Cheshire | Student | 7th - Evicted BB13 | Conor McIntyre | 24 | Derry | Personal Trainer | 8th - Walked BB13 | Becky Hannon | 19 | Blackburn | Student | 9th - Evicted BB13 | Caroline Wharram | 20 | London | Unemployed | 10th - Evicted BB13 | Lauren Carre | 20 | Jersey | Student | 11th - Evicted BB13 | Shievonne Robinson | 28 | London | Shop Assistant Manager | 12th - Evicted BB13 | Arron Lowe | 23 | Manchester | Model | 13th - Evicted BB13 | Lydia Louisa | 25 | Cheshire | Dancer | 14th - Evicted BB13 | Benedict Garrett | 32 | Manchester | Stripper/Porn Star | 15th - Evicted BB13 | Chris James | 21 | Luton | Doorman | 16th - Evicted BB13 | Victoria Eisermann | 41 | Reading | Model/Animal Rights Campaigner | 17th - Evicted BB14 | Sam Evans | 23 | Llanelli | Stockroom Assistant | 1st - Winner BB14 | Dexter Koh | 28 | London | Celebrity publicist | 2nd - Runner-up BB14 | Gina Rio | 24 | London | Socialite | 3rd - Third Place BB14 | Jack and Joe Glenny | 18 | Hertfordshire | Supermarket checkout assistants | 4th - Evicted BB14 | Charlie Travers | 26 | Hertfordshire | Receptionist | 5th - Evicted BB14 | Sophie Lawrence | 20 | London | Dental Nurse | 6th - Evicted BB14 | Hazel O'Sullivan | 24 | Dublin | Glamour Model | 7th - Evicted BB14 | Callum Knell | 28 | Kent | Sports coach | 8th - Evicted BB14 | Dan Neal | 33 | London | Unemployed | 9th - Evicted BB14 | Jackie Travers | 59 | Hertfordshire | Dance Instructor | 10th - Evicted BB14 | Daley Ojuederie | 28 | London | Professional Boxer | 11th - Ejected BB14 | Wolfy Millington | 20 | Bolton | Student | 12th - Evicted BB14 | Jemima Slade | 41 | London | Dating website owner | 13th - Evicted BB14 | Sallie Axl | 26 | Wirral | Glamour Model | 14th - Evicted TBB | Paul Brennan | 18 | Belfast | Student | 1st - Winner TBB | Caroline Cloke | 18 | Kent | Student | 2nd - Runner-up TBB | Tracey Fowler | 18 | Cheshire | Student | 3rd - Third Place TBB | Tommy Wright | 18 | Dorset | Student | 4th - Evicted TBB | Jade Dyer | 18 | Suffolk | Student | 5th - Evicted TBB | James Kelly | 18 | Glasgow | Student | 6th - Ejected TBB | Shaneen Dawkins | 18 | Leeds | Student | 7th - Evicted TBB | Hasan Shah | 18 | London | Student | 8th - Evicted BB:CH | John Loughton | 20 | Edinburgh | Politician | 1st - Winner BB:CH | Emilia Arata | 18 | Birmingham | Circus Performer | 2nd - Runner-up BB:CH | Amy Jackson | 21 | Oxford | Conceptual Artist | 3rd - Third Place BB:CH | Anthony Ogogo | 19 | Suffolk | Boxer | 4th - Evicted BB:CH | Jeremy Metcalfe | 19 | Hampshire | Racing Driver | 5th - Evicted BB:CH | Nathan Fagan-Gayle | 21 | London | Singer/Songwriter | 6th - Evicted BB:CH | Calista Robertson | 19 | London | Classical Musician | 7th - Evicted BB:CH | Jay Wilson | 19 | London | Fashion Designer | 8th - Evicted BB:CH | Latoya Satnarine | 19 | London | Dancer | 9th - Evicted BB:CH | Victor Arata | 19 | Birmingham | Circus Performer | 10th - Evicted BB:CH | Liam Young | 19 | Liverpool | Entrepreneur | 11th - Evicted BB:CH | Jade Eden | 21 | London | Beauty Queen | 12th - Evicted BBP | Anouska Golebiewski | 22 | Manchester | Participated in BB4 | Not competing BBP | Jade Goody | 23 | London | Participated in BB3 | Not competing BBP | Kitten Pinder | 25 | Brighton | Participated in BB5 | Not competing BBP | Marco Sabba | 21 | Middlesex | Participated in BB5 | Not competing BBP | Mel (Melanie) Hill | 30 | London | Participated in BB1 | Not competing BBP | Narinder Kaur | 23 | Leicester | Participated in BB2 | Not competing BBP | Nick Bateman | 37 | Kent | Participated in BB1 | Not competing BBP | Spencer Smith | 25 | Cambridge | Participated in BB3 | Not competing BBP | Tim Culley | 22 | Worcester | Participated in BB3 | Not competing BBP | Victor Ebuwa | 23 | London | Participated in BB5 | Not competing UBB | Brian Dowling | 32 | County Kildare | Participated in BB2 | 1st - Winner UBB | Nikki Grahame | 28 | London | Participated in BB7 | 2nd - Runner-up UBB | Chantelle Houghton | 27 | Essex | Participated in CBB5 | 3rd - Third Place UBB | Victor Ebuwa | 29 | London | Participated in BB5 | 4th - Evicted UBB | Nick Bateman | 42 | Kent | Participated in BB1 | 5th - Evicted UBB | Preston | 28 | Brighton | Participated in CBB4 | 6th - Evicted UBB | Ulrika Jonsson | 43 | Buckinghamshire | Participated in CBB6 | 7th - Evicted UBB | Vanessa Feltz | 48 | London | Participated in CBB1 | 8th - Evicted UBB | Michelle Bass | 29 | Newcastle | Participated in BB5 | 9th - Evicted UBB | Nadia Almada | 33 | London | Participated in BB5 | 10th - Evicted UBB | Makosi Musambasi | 29 | Buckinghamshire | Participated in BB6 | 11th - Evicted UBB | Coolio | 47 | Pennsylvania, USA | Participated in CBB6 | 12th - Ejected UBB | John McCririck | 70 | London | Participated in CBB3 | 13th - Evicted UBB | Josie Gibson | 25 | Bristol | Participated in BB11 | 14th - Walked
Please identify the row and column numbers of the table displayed in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_227
WTQ_204-csv_818.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Wrestler: | Reigns: | Date: | Place: | Notes: Ron Starr | 1 | September 19, 1986 | Ponce, Puerto Rico | Defeated Invader I in a Tournament Final Invader I | 1 | November 5, 1986 | San Juan, Puerto Rico | Jason The Terrible | 1 | January 17, 1987 | Caguas, Puerto Rico | Invader I | 2 | September 18, 1987 | San Juan, Puerto Rico | Grizzly Boone | 1 | October 24, 1987 | Bayamon, Puerto Rico | Invader I | 3 | November 25, 1987 | San Juan, Puerto Rico | Held up after a match against Super Black Ninja on January 8, 1988 in San Juan, PR Super Black Ninja | 1 | February 6, 1988 | Guaynabo, Puerto Rico | Invader I | 4 | April 2, 1988 | Bayamon, Puerto Rico | Ron Starr | 2 | June 25, 1988 | Carolina, Puerto Rico | Carlos Colon | 1 | August 20, 1988 | Bayamon, Puerto Rico | Jason The Terrible | 2 | January 28, 1989 | Carolina, Puerto Rico | Carlos Colon | 2 | March 1, 1989 | Carolina, Puerto Rico | Vacant on May 22, 1989 after Colon was injured by Steve Strong on May 20, 1989 TNT | 1 | June 17, 1989 | San Juan, Puerto Rico | Defeats Abudda Dein; vacant on February 9, 1990 when TNT wins the WWC Universal Heavyweight Title Leo Burke | 1 | March 24, 1990 | Caguas, Puerto Rico | Defeats Carlos Colon in a tournament final. TNT | 2 | April 25, 1990 | San Juan, Puerto Rico | Won the vacant title Action Jackson (Original TNT) | 1 | January 26, 1991 | Caguas, Puerto Rico | Wins tournament; loses a name match on March 2, 1991 in Bayamon, PR TNT | 3 | March 30, 1991 | Bayamon, Puerto Rico | King Kong | 1 | April 20, 1991 | Bayamon, Puerto Rico | TNT | 4 | June 1, 1991 | Bayamon, Puerto Rico | Fidel Sierra | 1 | October 19, 1991 | Bayamon, Puerto Rico | TNT | 5 | October 26, 1991 | Carolina, Puerto Rico | Dick Murdoch | 1 | November 23, 1991 | Arroyo, Puerto Rico | Invader I | 5 | December 25, 1991 | San Juan, Puerto Rico | Dick Murdoch | 2 | January 6, 1992 | San Juan, Puerto Rico | Vacant on January 6, 1993 when Murdoch leaves the promotion. Carlos Colon | 3 | June 18, 1994 | San Juan, Puerto Rico | Defeated Mighty Koadiak in a tournament final. Mighty Koadiak | 1 | 1994 | | Rex King | 1 | 1995 | | Sean Morley | 1 | 1995 | | Ricky Santana | 1 | 1995 | | Rex King | 2 | 1995 | | Pulgarcito | 1 | November 11, 1995 | | Mighty Koadiak | 2 | November 26, 1995 | | Sweet Brown Sugar (Skip Young) | 1 | January 6, 1996 | Caguas, Puerto Rico | Ricky Santana | 2 | March 23, 1996 | Caguas, Puerto Rico | \Jungle\" Jim Steele" | 1 | April 20, 1996 | Caguas, Puerto Rico | El Bronco I | 1 | May 18, 1996 | Caguas, Puerto Rico | Sean Morley | 2 | May 30, 1996 | Caguas, Puerto Rico | Joins the WWF in 1997, but is still recognized as champion; title becomes vacant on March 3, 1999. Glamour Boy Shane | 1 | April 2, 1999 | Guaynabo, Puerto Rico | Defeated \Jungle\" Jim Steele for vacant title." Mustafa Saed | 1 | August 14, 1999 | Caguas, Puerto Rico | Glamour Boy Shane | 2 | September 19, 1999 | Guaynabo, Puerto Rico | Chicky Starr | 1 | November 13, 1999 | Naguabo, Puerto Rico | Glamour Boy Shane | 3 | January 6, 2000 | Caguas, Puerto Rico | Rex King | 3 | March 19, 2000 | Cabo Rojo, Puerto Rico | Chris Grant | 1 | April 21, 2001 | Orocovis, Puerto Rico | Alex Porteau | 1 | July 7, 2001 | Carolina, Puerto Rico | Chris Grant | 2 | July 21, 2001 | Orocovis, Puerto Rico | wins the title by forfeit Bad Boy Bradley | 1 | September 8, 2001 | Bayamón, Puerto Rico | Super Gladiator | 1 | October 6, 2001 | Caguas, Puerto Rico | Ricky Santana | 3 | March 16, 2002 | Aibonito, Puerto Rico | Rico Suave | 1 | April 6, 2002 | Caguas, Puerto Rico | Ray Gonzalez | 1 | April 27, 2002 | San Lorenzo, Puerto Rico | Carlos Colon | 4 | June 8, 2002 | Toa Baja, Puerto Rico | Ray Gonzalez | 2 | June 15, 2002 | Caguas, Puerto Rico | Vacates title on July 1, 2002 when he leaves the company. Wilfredo Alejandro | 1 | July 6, 2002 | Cayey, Puerto Rico | wins a battle royal for the vacant title. Fidel Sierra | 2 | August 24, 2002 | Coamo, Puerto Rico | Chris Candido | 1 | June 6, 2003 | Cayey, Puerto Rico | Vengador Boricua | 1 | July 19, 2003 | Carolina, Puerto Rico | title becomes inactive when Vengador Boricua leaves the company. Superstar Romeo | 1 | February 3, 2007 | Caguas, Puerto Rico | Romeo beat Barabas Jr. to win the reactivated title. Rico Suave | 2 | March 17, 2007 | Bayamon, Puerto Rico | Crazy Rudy | 1 | April 28, 2007 | Bayamon, Puerto Rico | Ash Rubinsky | 1 | November 24, 2007 | Bayamon, Puerto Rico | Wins a 7-man battle royal. B.J. | 1 | January 6, 2008 | Choliseo, Puerto Rico | Wins the title after winning an 11 man Battle Royal Hammett | 1 | March 1, 2008 | Tao Baja, Puerto Rico | B.J. | 2 | March 15, 2008 | Lares, Puerto Rico | Chris Joel | 1 | May 10, 2008 | Bayamon, Puerto Rico | Vacant | | | | Chris Joel Jumps to IWA
WTQ_for_TSD
Wrestler: | Reigns: | Date: | Place: | Notes: Ron Starr | 1 | September 19, 1986 | Ponce, Puerto Rico | Defeated Invader I in a Tournament Final Invader I | 1 | November 5, 1986 | San Juan, Puerto Rico | Jason The Terrible | 1 | January 17, 1987 | Caguas, Puerto Rico | Invader I | 2 | September 18, 1987 | San Juan, Puerto Rico | Grizzly Boone | 1 | October 24, 1987 | Bayamon, Puerto Rico | Invader I | 3 | November 25, 1987 | San Juan, Puerto Rico | Held up after a match against Super Black Ninja on January 8, 1988 in San Juan, PR Super Black Ninja | 1 | February 6, 1988 | Guaynabo, Puerto Rico | Invader I | 4 | April 2, 1988 | Bayamon, Puerto Rico | Ron Starr | 2 | June 25, 1988 | Carolina, Puerto Rico | Carlos Colon | 1 | August 20, 1988 | Bayamon, Puerto Rico | Jason The Terrible | 2 | January 28, 1989 | Carolina, Puerto Rico | Carlos Colon | 2 | March 1, 1989 | Carolina, Puerto Rico | Vacant on May 22, 1989 after Colon was injured by Steve Strong on May 20, 1989 TNT | 1 | June 17, 1989 | San Juan, Puerto Rico | Defeats Abudda Dein; vacant on February 9, 1990 when TNT wins the WWC Universal Heavyweight Title Leo Burke | 1 | March 24, 1990 | Caguas, Puerto Rico | Defeats Carlos Colon in a tournament final. TNT | 2 | April 25, 1990 | San Juan, Puerto Rico | Won the vacant title Action Jackson (Original TNT) | 1 | January 26, 1991 | Caguas, Puerto Rico | Wins tournament; loses a name match on March 2, 1991 in Bayamon, PR TNT | 3 | March 30, 1991 | Bayamon, Puerto Rico | King Kong | 1 | April 20, 1991 | Bayamon, Puerto Rico | TNT | 4 | June 1, 1991 | Bayamon, Puerto Rico | Fidel Sierra | 1 | October 19, 1991 | Bayamon, Puerto Rico | TNT | 5 | October 26, 1991 | Carolina, Puerto Rico | Dick Murdoch | 1 | November 23, 1991 | Arroyo, Puerto Rico | Invader I | 5 | December 25, 1991 | San Juan, Puerto Rico | Dick Murdoch | 2 | January 6, 1992 | San Juan, Puerto Rico | Vacant on January 6, 1993 when Murdoch leaves the promotion. Carlos Colon | 3 | June 18, 1994 | San Juan, Puerto Rico | Defeated Mighty Koadiak in a tournament final. Mighty Koadiak | 1 | 1994 | | Rex King | 1 | 1995 | | Sean Morley | 1 | 1995 | | Ricky Santana | 1 | 1995 | | Rex King | 2 | 1995 | | Pulgarcito | 1 | November 11, 1995 | | Mighty Koadiak | 2 | November 26, 1995 | | Sweet Brown Sugar (Skip Young) | 1 | January 6, 1996 | Caguas, Puerto Rico | Ricky Santana | 2 | March 23, 1996 | Caguas, Puerto Rico | \Jungle\" Jim Steele" | 1 | April 20, 1996 | Caguas, Puerto Rico | El Bronco I | 1 | May 18, 1996 | Caguas, Puerto Rico | Sean Morley | 2 | May 30, 1996 | Caguas, Puerto Rico | Joins the WWF in 1997, but is still recognized as champion; title becomes vacant on March 3, 1999. Glamour Boy Shane | 1 | April 2, 1999 | Guaynabo, Puerto Rico | Defeated \Jungle\" Jim Steele for vacant title." Mustafa Saed | 1 | August 14, 1999 | Caguas, Puerto Rico | Glamour Boy Shane | 2 | September 19, 1999 | Guaynabo, Puerto Rico | Chicky Starr | 1 | November 13, 1999 | Naguabo, Puerto Rico | Glamour Boy Shane | 3 | January 6, 2000 | Caguas, Puerto Rico | Rex King | 3 | March 19, 2000 | Cabo Rojo, Puerto Rico | Chris Grant | 1 | April 21, 2001 | Orocovis, Puerto Rico | Alex Porteau | 1 | July 7, 2001 | Carolina, Puerto Rico | Chris Grant | 2 | July 21, 2001 | Orocovis, Puerto Rico | wins the title by forfeit Bad Boy Bradley | 1 | September 8, 2001 | Bayamón, Puerto Rico | Super Gladiator | 1 | October 6, 2001 | Caguas, Puerto Rico | Ricky Santana | 3 | March 16, 2002 | Aibonito, Puerto Rico | Rico Suave | 1 | April 6, 2002 | Caguas, Puerto Rico | Ray Gonzalez | 1 | April 27, 2002 | San Lorenzo, Puerto Rico | Carlos Colon | 4 | June 8, 2002 | Toa Baja, Puerto Rico | Ray Gonzalez | 2 | June 15, 2002 | Caguas, Puerto Rico | Vacates title on July 1, 2002 when he leaves the company. Wilfredo Alejandro | 1 | July 6, 2002 | Cayey, Puerto Rico | wins a battle royal for the vacant title. Fidel Sierra | 2 | August 24, 2002 | Coamo, Puerto Rico | Chris Candido | 1 | June 6, 2003 | Cayey, Puerto Rico | Vengador Boricua | 1 | July 19, 2003 | Carolina, Puerto Rico | title becomes inactive when Vengador Boricua leaves the company. Superstar Romeo | 1 | February 3, 2007 | Caguas, Puerto Rico | Romeo beat Barabas Jr. to win the reactivated title. Rico Suave | 2 | March 17, 2007 | Bayamon, Puerto Rico | Crazy Rudy | 1 | April 28, 2007 | Bayamon, Puerto Rico | Ash Rubinsky | 1 | November 24, 2007 | Bayamon, Puerto Rico | Wins a 7-man battle royal. B.J. | 1 | January 6, 2008 | Choliseo, Puerto Rico | Wins the title after winning an 11 man Battle Royal Hammett | 1 | March 1, 2008 | Tao Baja, Puerto Rico | B.J. | 2 | March 15, 2008 | Lares, Puerto Rico | Chris Joel | 1 | May 10, 2008 | Bayamon, Puerto Rico | Vacant | | | | Chris Joel Jumps to IWA
For the table shown in this image, can you tell me the row and column numbers of this table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_228
WTQ_204-csv_65.jpg
I need to know the count of rows and columns in this specific table. Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> Rank | Lane | Name | Nationality | Time | Notes 1 | 5 | Eskender Mustafaiev | Ukraine | 38.77 | Q 2 | 4 | David Smetanine | France | 38.97 | Q 3 | 3 | Kyunghyun Kim | South Korea | 40.37 | Q 4 | 6 | Christoffer Lindhe | Sweden | 41.52 | Q 5 | 7 | Arnost Petracek | Czech Republic | 43.12 | 6 | 2 | Ronystony Cordeiro da Silva | Brazil | 44.22 | 7 | 8 | Grant Patterson | Australia | 55.49 | 8 | 1 | Arnulfo Castorena | Mexico | 1:03.49 |
WTQ_for_TSD
Rank | Lane | Name | Nationality | Time | Notes 1 | 5 | Eskender Mustafaiev | Ukraine | 38.77 | Q 2 | 4 | David Smetanine | France | 38.97 | Q 3 | 3 | Kyunghyun Kim | South Korea | 40.37 | Q 4 | 6 | Christoffer Lindhe | Sweden | 41.52 | Q 5 | 7 | Arnost Petracek | Czech Republic | 43.12 | 6 | 2 | Ronystony Cordeiro da Silva | Brazil | 44.22 | 7 | 8 | Grant Patterson | Australia | 55.49 | 8 | 1 | Arnulfo Castorena | Mexico | 1:03.49 |
I need to know the count of rows and columns in this specific table. Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_229
WTQ_204-csv_531.jpg
I need to know the count of rows and columns in this specific table. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Team | Chassis | Engine | Tires | No | Drivers Chip Ganassi Racing | Reynard 98i | Honda | Firestone | 1 | Alex Zanardi Chip Ganassi Racing | Reynard 98i | Honda | Firestone | 12 | Jimmy Vasser Marlboro Team Penske | Penske PC27-98 | Mercedes | Goodyear | 2 | Al Unser, Jr. Marlboro Team Penske | Penske PC27-98 | Mercedes | Goodyear | 3 | André Ribeiro Walker Racing | Reynard 98i | Honda | Goodyear | 5 | Gil de Ferran Newman-Haas Racing | Swift 009.c | Ford XB | Goodyear | 6 | Michael Andretti Newman-Haas Racing | Swift 009.c | Ford XB | Goodyear | 11 | Christian Fittipaldi Roberto Moreno Team Rahal | Reynard 98i | Ford XB | Firestone | 7 | Bobby Rahal Team Rahal | Reynard 98i | Ford XB | Firestone | 8 | Bryan Herta Hogan Racing | Reynard 98i | Mercedes | Firestone | 9 | JJ Lehto Della Penna Motorsports | Swift 009.c | Ford XB | Firestone | 10 | Richie Hearn Della Penna Motorsports | Swift 009.c | Ford XB | Firestone | 43 | Hideshi Matsuda Project Indy | Reynard 97i | Ford XB | Goodyear | 15 | Roberto Moreno Domenico Schiattarella Bettenhausen Racing | Reynard 98i | Mercedes | Goodyear | 16 | Hélio Castroneves PacWest Racing Group | Reynard 98i | Mercedes | Firestone | 17 | Maurício Gugelmin PacWest Racing Group | Reynard 98i | Mercedes | Firestone | 18 | Mark Blundell Payton/Coyne Racing | Reynard 98i | Ford XB | Firestone | 19 | Michel Jourdain, Jr. Payton/Coyne Racing | Reynard 98i | Ford XB | Firestone | 34 | Dennis Vitolo Gualter Salles Patrick Racing | Reynard 98i | Ford XB | Firestone | 20 | Scott Pruett Patrick Racing | Reynard 98i | Ford XB | Firestone | 40 | Adrián Fernández Tasman Motorsports Group | Reynard 98i | Honda | Firestone | 21 | Tony Kanaan Arciero-Wells Racing | Reynard 98i | Toyota | Firestone | 24 | Hiro Matsushita Robby Gordon Arciero-Wells Racing | Reynard 98i | Toyota | Firestone | 25 | Max Papis Team KOOL Green | Reynard 98i | Honda | Firestone | 26 | Paul Tracy Team KOOL Green | Reynard 98i | Honda | Firestone | 27 | Dario Franchitti Forsythe Racing | Reynard 98i | Mercedes | Firestone | 33 | Patrick Carpentier Forsythe Racing | Reynard 98i | Mercedes | Firestone | 99 | Greg Moore All American Racing | Reynard 98i Eagle 987 | Toyota | Goodyear | 36 | Alex Barron All American Racing | Reynard 98i Eagle 987 | Toyota | Goodyear | 98 | P. J. Jones Vincenzo Sospiri Davis Racing | Lola T98/00 | Ford XB | Goodyear | 77 | Arnd Meier
WTQ_for_TSD
Team | Chassis | Engine | Tires | No | Drivers Chip Ganassi Racing | Reynard 98i | Honda | Firestone | 1 | Alex Zanardi Chip Ganassi Racing | Reynard 98i | Honda | Firestone | 12 | Jimmy Vasser Marlboro Team Penske | Penske PC27-98 | Mercedes | Goodyear | 2 | Al Unser, Jr. Marlboro Team Penske | Penske PC27-98 | Mercedes | Goodyear | 3 | André Ribeiro Walker Racing | Reynard 98i | Honda | Goodyear | 5 | Gil de Ferran Newman-Haas Racing | Swift 009.c | Ford XB | Goodyear | 6 | Michael Andretti Newman-Haas Racing | Swift 009.c | Ford XB | Goodyear | 11 | Christian Fittipaldi Roberto Moreno Team Rahal | Reynard 98i | Ford XB | Firestone | 7 | Bobby Rahal Team Rahal | Reynard 98i | Ford XB | Firestone | 8 | Bryan Herta Hogan Racing | Reynard 98i | Mercedes | Firestone | 9 | JJ Lehto Della Penna Motorsports | Swift 009.c | Ford XB | Firestone | 10 | Richie Hearn Della Penna Motorsports | Swift 009.c | Ford XB | Firestone | 43 | Hideshi Matsuda Project Indy | Reynard 97i | Ford XB | Goodyear | 15 | Roberto Moreno Domenico Schiattarella Bettenhausen Racing | Reynard 98i | Mercedes | Goodyear | 16 | Hélio Castroneves PacWest Racing Group | Reynard 98i | Mercedes | Firestone | 17 | Maurício Gugelmin PacWest Racing Group | Reynard 98i | Mercedes | Firestone | 18 | Mark Blundell Payton/Coyne Racing | Reynard 98i | Ford XB | Firestone | 19 | Michel Jourdain, Jr. Payton/Coyne Racing | Reynard 98i | Ford XB | Firestone | 34 | Dennis Vitolo Gualter Salles Patrick Racing | Reynard 98i | Ford XB | Firestone | 20 | Scott Pruett Patrick Racing | Reynard 98i | Ford XB | Firestone | 40 | Adrián Fernández Tasman Motorsports Group | Reynard 98i | Honda | Firestone | 21 | Tony Kanaan Arciero-Wells Racing | Reynard 98i | Toyota | Firestone | 24 | Hiro Matsushita Robby Gordon Arciero-Wells Racing | Reynard 98i | Toyota | Firestone | 25 | Max Papis Team KOOL Green | Reynard 98i | Honda | Firestone | 26 | Paul Tracy Team KOOL Green | Reynard 98i | Honda | Firestone | 27 | Dario Franchitti Forsythe Racing | Reynard 98i | Mercedes | Firestone | 33 | Patrick Carpentier Forsythe Racing | Reynard 98i | Mercedes | Firestone | 99 | Greg Moore All American Racing | Reynard 98i Eagle 987 | Toyota | Goodyear | 36 | Alex Barron All American Racing | Reynard 98i Eagle 987 | Toyota | Goodyear | 98 | P. J. Jones Vincenzo Sospiri Davis Racing | Lola T98/00 | Ford XB | Goodyear | 77 | Arnd Meier
I need to know the count of rows and columns in this specific table. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_230
WTQ_204-csv_502.jpg
I need to know the count of rows and columns in this specific table. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Year | Winner | Age | Jockey | Trainer | Owner | Distance (Miles) | Time | Purse | Gr 2014 | Constitution | 3 | Javier Castellano | Todd Pletcher | Winstar Farm | 1-1/8 | 1:49.17 | $1,000,000 | I 2013 | Orb | 3 | John Velazquez | Claude McGaughey III | Janney/Phipps Stable | 1-1/8 | 1:50.87 | $1,000,000 | I 2012 | Take Charge Indy | 3 | Calvin Borel | Patrick B. Byrne | C & M Sandford | 1-1/8 | 1:48.79 | $1,000,000 | I 2011 | Dialed In | 3 | Julien R. Leparoux | Nick Zito | Robert V. LaPenta | 1-1/8 | 1:50.74 | $1,000,000 | I 2010 | Ice Box | 3 | Jose Lezcano | Nick Zito | Robert V. LaPenta | 1-1/8 | 1:49.19 | $750,000 | I 2009 | Quality Road | 3 | John Velazquez | James A. Jerkens | Edward P. Evans | 1-1/8 | 1:47.72 | $750,000 | I 2008 | Big Brown | 3 | Kent Desormeaux | Richard E. Dutrow | IEAH Stables/Paul Pompa | 1-1/8 | 1:48.16 | $1,000,000 | I 2007 | Scat Daddy | 3 | Edgar Prado | Todd A. Pletcher | J. Scatuorchio / M. Tabor | 1-1/8 | 1:49.00 | $1,000,000 | I 2006 | Barbaro | 3 | Edgar Prado | Michael Matz | Lael Stables | 1-1/8 | 1:49.01 | $1,000,000 | I 2005 | High Fly | 3 | Jerry Bailey | Nick Zito | Live Oak Plantation | 1-1/8 | 1:49.43 | $1,000,000 | I 2004 | Friends Lake | 3 | Richard Migliore | John C. Kimmel | Chester & Mary Broman | 1-1/8 | 1:51.38 | $1,000,000 | I 2003 | Empire Maker | 3 | Jerry Bailey | Robert Frankel | Juddmonte Farms | 1-1/8 | 1:49.05 | $1,000,000 | I 2002 | Harlan's Holiday | 3 | Edgar Prado | Kenneth McPeek | Starlight Stable | 1-1/8 | 1:48.80 | $1,000,000 | I 2001 | Monarchos | 3 | Jorge Chavez | John T. Ward, Jr. | John C. Oxley | 1-1/8 | 1:49.95 | $1,000,000 | I 2000 | Hal's Hope | 3 | Roger Velez | Harold Rose | Rose Family Stable | 1-1/8 | 1:51.49 | $1,000,000 | I 1999 | Vicar | 3 | Shane Sellers | Carl Nafzger | James B. Tafel | 1-1/8 | 1:50.83 | $750,000 | I 1998 | Cape Town † | 3 | Shane Sellers | D. Wayne Lukas | Overbrook Farm | 1-1/8 | 1:49.21 | $750,000 | I 1997 | Captain Bodgit | 3 | Alex Solis | Gary Capuano | Team Valor | 1-1/8 | 1:50.60 | $750,000 | I 1996 | Unbridled's Song | 3 | Mike Smith | James T. Ryerson | Paraneck Stable | 1-1/8 | 1:47.85 | $750,000 | I 1995 | Thunder Gulch | 3 | Mike Smith | D. Wayne Lukas | Michael Tabor | 1-1/8 | 1:49.70 | $500,000 | I 1994 | Holy Bull | 3 | Mike Smith | Warren A. Croll, Jr. | Warren A. Croll, Jr. | 1-1/8 | 1:47.66 | $500,000 | I 1993 | Bull In the Heather | 3 | Wigberto Ramos | Howard M. Tesher | Arthur Klein | 1-1/8 | 1:51.38 | $500,000 | I 1992 | Technology | 3 | Jerry Bailey | Hubert Hine | Scott Savin | 1-1/8 | 1:50.72 | $500,000 | I 1991 | Fly So Free | 3 | Jose Santos | Scotty Schulhofer | Tommy Valando | 1-1/8 | 1:50.44 | $500,000 | I 1990 | Unbridled | 3 | Pat Day | Carl Nafzger | Genter Stable | 1-1/8 | 1:52.00 | $500,000 | I 1989 | Mercedes Won | 3 | Earlie Fires | Arnold Fink | Christopher Spencer | 1-1/8 | 1:49.60 | $500,000 | I 1988 | Brian's Time | 3 | Randy Romero | John M. Veitch | James W. Phillips | 1-1/8 | 1:49.80 | $500,000 | I 1987 | Cryptoclearance | 3 | Jose Santos | Scotty Schulhofer | Phil Teinowitz | 1-1/8 | 1:49.60 | $500,000 | I 1986 | Snow Chief | 3 | Alex Solis | Melvin F. Stute | Rochelle/Grinstead | 1-1/8 | 1:51.80 | $500,000 | I 1985 | Proud Truth | 3 | Jorge Velasquez | John M. Veitch | Darby Dan Farm | 1-1/8 | 1:50.00 | $500,000 | I 1984 | Swale | 3 | Laffit Pincay, Jr. | Woody Stephens | Claiborne Farm | 1-1/8 | 1:47.60 | $300,000 | I 1983 | Croeso | 3 | Frank Olivares | Jerry M. Fanning | Joyce & Roy Fowler | 1-1/8 | 1:49.80 | $300,000 | I 1982 | Timely Writer | 3 | Jeffrey Fell | Dominic Imprescia | Peter & Francis Martin | 1-1/8 | 1:49.60 | $250,000 | I 1981 | Lord Avie | 3 | Chris McCarron | Daniel Perlsweig | David Simon | 1-1/8 | 1:50.40 | $250,000 | I 1980 | Plugged Nickle | 3 | Buck Thornburg | Thomas J. Kelly | John M. Schiff | 1-1/8 | 1:50.20 | $250,000 | I 1979 | Spectacular Bid | 3 | Ronnie Franklin | Bud Delp | Hawksworth Farm | 1-1/8 | 1:48.80 | $200,000 | I 1978 | Alydar | 3 | Jorge Velasquez | John M. Veitch | Calumet Farm | 1-1/8 | 1:47.00 | $200,000 | I 1977 | Ruthie's Native | 3 | Craig Perret | Eugene Jacobs | Ruth A. Perlmutter | 1-1/8 | 1:50.20 | $125,000 | I 1977 | Coined Silver | 3 | Buck Thornburg | George T. Poole III | C. V. Whitney | 1-1/8 | 1:48.80 | $125,000 | I 1976 | Honest Pleasure | 3 | Braulio Baeza | LeRoy Jolley | Bertram R. Firestone | 1-1/8 | 1:47.80 | $125,000 | I 1975 | Prince Thou Art | 3 | Braulio Baeza | Lou Rondinello | Darby Dan Farm | 1-1/8 | 1:50.40 | $150,000 | I 1974 | Judger | 3 | Laffit Pincay, Jr. | Woody Stephens | Claiborne Farm | 1-1/8 | 1:49.00 | $150,000 | I 1973 | Royal and Regal | 3 | Walter Blum | Warren A. Croll, Jr. | Aisco Stable | 1-1/8 | 1:47.40 | $130,000 | I 1972 | Upper Case | 3 | Ron Turcotte | Lucien Laurin | Meadow Stable | 1-1/8 | 1:50.00 | $130,000 | 1971 | Eastern Fleet | 3 | Eddie Maple | Reggie Cornell | Calumet Farm | 1-1/8 | 1:47.40 | | 1970 | My Dad George | 3 | Ray Broussard | Frank J. McManus | Raymond M. Curtis | 1-1/8 | 1:50.80 | | 1969 | Top Knight | 3 | Manuel Ycaza | Ray Metcalf | Steven B. Wilson | 1-1/8 | 1:48.40 | | 1968 | Forward Pass | 3 | Don Brumfield | Henry Forrest | Calumet Farm | 1-1/8 | 1:49.00 | | 1967 | In Reality | 3 | Earlie Fires | Melvin Calvert | Frances A. Genter | 1-1/8 | 1:50.20 | | 1966 | Williamston Kid † | 3 | Robert Stevenson | James Bartlett | Ternes & Bartlett | 1-1/8 | 1:50.60 | | 1965 | Native Charger | 3 | John L. Rotz | Ray Metcalf | Warner Stable | 1-1/8 | 1:51.20 | | 1964 | Northern Dancer | 3 | Bill Shoemaker | Horatio Luro | Windfields Farm | 1-1/8 | 1:50.80 | | 1963 | Candy Spots | 3 | Bill Shoemaker | Mesh Tenney | Rex C. Ellsworth | 1-1/8 | 1:50.60 | | 1962 | Ridan | 3 | Manuel Ycaza | LeRoy Jolley | Jolley / Woods / Greer | 1-1/8 | 1:50.40 | | 1961 | Carry Back | 3 | Johnny Sellers | Jack A. Price | Mrs. Katherine Price | 1-1/8 | 1:48.80 | | 1960 | Bally Ache | 3 | Bobby Ussery | Homer Pitt | Edgehill Farm | 1-1/8 | 1:47.60 | | 1959 | Easy Spur | 3 | Bill Hartack | Paul L. Kelley | Spring Hill Farm | 1-1/8 | 1:47.20 | | 1958 | Tim Tam | 3 | Bill Hartack | Horace A. Jones | Calumet Farm | 1-1/8 | 1:49.20 | | 1957 | Gen. Duke | 3 | Bill Hartack | Horace A. Jones | Calumet Farm | 1-1/8 | 1:46.80 | | 1956 | Needles | 3 | David Erb | Hugh L. Fontaine | D & H Stable | 1-1/8 | 1:48.60 | | 1955 | Nashua | 3 | Eddie Arcaro | Jim Fitzsimmons | Belair Stud | 1-1/8 | 1:53.20 | | 1954 | Correlation | 3 | Bill Shoemaker | Noble Threewitt | Robert S. Lytle | 1-1/8 | 1:55.20 | | 1953 | Money Broker | 3 | Alfred Popara | Vester R. Wright | G. & G. Stable | 1-1/8 | 1:53.80 | | 1952 | Sky Ship | 3 | Ronnie Nash | Preston M. Burch | Brookmeade Stable | 1-1/8 | 1:50.80 | |
WTQ_for_TSD
Year | Winner | Age | Jockey | Trainer | Owner | Distance (Miles) | Time | Purse | Gr 2014 | Constitution | 3 | Javier Castellano | Todd Pletcher | Winstar Farm | 1-1/8 | 1:49.17 | $1,000,000 | I 2013 | Orb | 3 | John Velazquez | Claude McGaughey III | Janney/Phipps Stable | 1-1/8 | 1:50.87 | $1,000,000 | I 2012 | Take Charge Indy | 3 | Calvin Borel | Patrick B. Byrne | C & M Sandford | 1-1/8 | 1:48.79 | $1,000,000 | I 2011 | Dialed In | 3 | Julien R. Leparoux | Nick Zito | Robert V. LaPenta | 1-1/8 | 1:50.74 | $1,000,000 | I 2010 | Ice Box | 3 | Jose Lezcano | Nick Zito | Robert V. LaPenta | 1-1/8 | 1:49.19 | $750,000 | I 2009 | Quality Road | 3 | John Velazquez | James A. Jerkens | Edward P. Evans | 1-1/8 | 1:47.72 | $750,000 | I 2008 | Big Brown | 3 | Kent Desormeaux | Richard E. Dutrow | IEAH Stables/Paul Pompa | 1-1/8 | 1:48.16 | $1,000,000 | I 2007 | Scat Daddy | 3 | Edgar Prado | Todd A. Pletcher | J. Scatuorchio / M. Tabor | 1-1/8 | 1:49.00 | $1,000,000 | I 2006 | Barbaro | 3 | Edgar Prado | Michael Matz | Lael Stables | 1-1/8 | 1:49.01 | $1,000,000 | I 2005 | High Fly | 3 | Jerry Bailey | Nick Zito | Live Oak Plantation | 1-1/8 | 1:49.43 | $1,000,000 | I 2004 | Friends Lake | 3 | Richard Migliore | John C. Kimmel | Chester & Mary Broman | 1-1/8 | 1:51.38 | $1,000,000 | I 2003 | Empire Maker | 3 | Jerry Bailey | Robert Frankel | Juddmonte Farms | 1-1/8 | 1:49.05 | $1,000,000 | I 2002 | Harlan's Holiday | 3 | Edgar Prado | Kenneth McPeek | Starlight Stable | 1-1/8 | 1:48.80 | $1,000,000 | I 2001 | Monarchos | 3 | Jorge Chavez | John T. Ward, Jr. | John C. Oxley | 1-1/8 | 1:49.95 | $1,000,000 | I 2000 | Hal's Hope | 3 | Roger Velez | Harold Rose | Rose Family Stable | 1-1/8 | 1:51.49 | $1,000,000 | I 1999 | Vicar | 3 | Shane Sellers | Carl Nafzger | James B. Tafel | 1-1/8 | 1:50.83 | $750,000 | I 1998 | Cape Town † | 3 | Shane Sellers | D. Wayne Lukas | Overbrook Farm | 1-1/8 | 1:49.21 | $750,000 | I 1997 | Captain Bodgit | 3 | Alex Solis | Gary Capuano | Team Valor | 1-1/8 | 1:50.60 | $750,000 | I 1996 | Unbridled's Song | 3 | Mike Smith | James T. Ryerson | Paraneck Stable | 1-1/8 | 1:47.85 | $750,000 | I 1995 | Thunder Gulch | 3 | Mike Smith | D. Wayne Lukas | Michael Tabor | 1-1/8 | 1:49.70 | $500,000 | I 1994 | Holy Bull | 3 | Mike Smith | Warren A. Croll, Jr. | Warren A. Croll, Jr. | 1-1/8 | 1:47.66 | $500,000 | I 1993 | Bull In the Heather | 3 | Wigberto Ramos | Howard M. Tesher | Arthur Klein | 1-1/8 | 1:51.38 | $500,000 | I 1992 | Technology | 3 | Jerry Bailey | Hubert Hine | Scott Savin | 1-1/8 | 1:50.72 | $500,000 | I 1991 | Fly So Free | 3 | Jose Santos | Scotty Schulhofer | Tommy Valando | 1-1/8 | 1:50.44 | $500,000 | I 1990 | Unbridled | 3 | Pat Day | Carl Nafzger | Genter Stable | 1-1/8 | 1:52.00 | $500,000 | I 1989 | Mercedes Won | 3 | Earlie Fires | Arnold Fink | Christopher Spencer | 1-1/8 | 1:49.60 | $500,000 | I 1988 | Brian's Time | 3 | Randy Romero | John M. Veitch | James W. Phillips | 1-1/8 | 1:49.80 | $500,000 | I 1987 | Cryptoclearance | 3 | Jose Santos | Scotty Schulhofer | Phil Teinowitz | 1-1/8 | 1:49.60 | $500,000 | I 1986 | Snow Chief | 3 | Alex Solis | Melvin F. Stute | Rochelle/Grinstead | 1-1/8 | 1:51.80 | $500,000 | I 1985 | Proud Truth | 3 | Jorge Velasquez | John M. Veitch | Darby Dan Farm | 1-1/8 | 1:50.00 | $500,000 | I 1984 | Swale | 3 | Laffit Pincay, Jr. | Woody Stephens | Claiborne Farm | 1-1/8 | 1:47.60 | $300,000 | I 1983 | Croeso | 3 | Frank Olivares | Jerry M. Fanning | Joyce & Roy Fowler | 1-1/8 | 1:49.80 | $300,000 | I 1982 | Timely Writer | 3 | Jeffrey Fell | Dominic Imprescia | Peter & Francis Martin | 1-1/8 | 1:49.60 | $250,000 | I 1981 | Lord Avie | 3 | Chris McCarron | Daniel Perlsweig | David Simon | 1-1/8 | 1:50.40 | $250,000 | I 1980 | Plugged Nickle | 3 | Buck Thornburg | Thomas J. Kelly | John M. Schiff | 1-1/8 | 1:50.20 | $250,000 | I 1979 | Spectacular Bid | 3 | Ronnie Franklin | Bud Delp | Hawksworth Farm | 1-1/8 | 1:48.80 | $200,000 | I 1978 | Alydar | 3 | Jorge Velasquez | John M. Veitch | Calumet Farm | 1-1/8 | 1:47.00 | $200,000 | I 1977 | Ruthie's Native | 3 | Craig Perret | Eugene Jacobs | Ruth A. Perlmutter | 1-1/8 | 1:50.20 | $125,000 | I 1977 | Coined Silver | 3 | Buck Thornburg | George T. Poole III | C. V. Whitney | 1-1/8 | 1:48.80 | $125,000 | I 1976 | Honest Pleasure | 3 | Braulio Baeza | LeRoy Jolley | Bertram R. Firestone | 1-1/8 | 1:47.80 | $125,000 | I 1975 | Prince Thou Art | 3 | Braulio Baeza | Lou Rondinello | Darby Dan Farm | 1-1/8 | 1:50.40 | $150,000 | I 1974 | Judger | 3 | Laffit Pincay, Jr. | Woody Stephens | Claiborne Farm | 1-1/8 | 1:49.00 | $150,000 | I 1973 | Royal and Regal | 3 | Walter Blum | Warren A. Croll, Jr. | Aisco Stable | 1-1/8 | 1:47.40 | $130,000 | I 1972 | Upper Case | 3 | Ron Turcotte | Lucien Laurin | Meadow Stable | 1-1/8 | 1:50.00 | $130,000 | 1971 | Eastern Fleet | 3 | Eddie Maple | Reggie Cornell | Calumet Farm | 1-1/8 | 1:47.40 | | 1970 | My Dad George | 3 | Ray Broussard | Frank J. McManus | Raymond M. Curtis | 1-1/8 | 1:50.80 | | 1969 | Top Knight | 3 | Manuel Ycaza | Ray Metcalf | Steven B. Wilson | 1-1/8 | 1:48.40 | | 1968 | Forward Pass | 3 | Don Brumfield | Henry Forrest | Calumet Farm | 1-1/8 | 1:49.00 | | 1967 | In Reality | 3 | Earlie Fires | Melvin Calvert | Frances A. Genter | 1-1/8 | 1:50.20 | | 1966 | Williamston Kid † | 3 | Robert Stevenson | James Bartlett | Ternes & Bartlett | 1-1/8 | 1:50.60 | | 1965 | Native Charger | 3 | John L. Rotz | Ray Metcalf | Warner Stable | 1-1/8 | 1:51.20 | | 1964 | Northern Dancer | 3 | Bill Shoemaker | Horatio Luro | Windfields Farm | 1-1/8 | 1:50.80 | | 1963 | Candy Spots | 3 | Bill Shoemaker | Mesh Tenney | Rex C. Ellsworth | 1-1/8 | 1:50.60 | | 1962 | Ridan | 3 | Manuel Ycaza | LeRoy Jolley | Jolley / Woods / Greer | 1-1/8 | 1:50.40 | | 1961 | Carry Back | 3 | Johnny Sellers | Jack A. Price | Mrs. Katherine Price | 1-1/8 | 1:48.80 | | 1960 | Bally Ache | 3 | Bobby Ussery | Homer Pitt | Edgehill Farm | 1-1/8 | 1:47.60 | | 1959 | Easy Spur | 3 | Bill Hartack | Paul L. Kelley | Spring Hill Farm | 1-1/8 | 1:47.20 | | 1958 | Tim Tam | 3 | Bill Hartack | Horace A. Jones | Calumet Farm | 1-1/8 | 1:49.20 | | 1957 | Gen. Duke | 3 | Bill Hartack | Horace A. Jones | Calumet Farm | 1-1/8 | 1:46.80 | | 1956 | Needles | 3 | David Erb | Hugh L. Fontaine | D & H Stable | 1-1/8 | 1:48.60 | | 1955 | Nashua | 3 | Eddie Arcaro | Jim Fitzsimmons | Belair Stud | 1-1/8 | 1:53.20 | | 1954 | Correlation | 3 | Bill Shoemaker | Noble Threewitt | Robert S. Lytle | 1-1/8 | 1:55.20 | | 1953 | Money Broker | 3 | Alfred Popara | Vester R. Wright | G. & G. Stable | 1-1/8 | 1:53.80 | | 1952 | Sky Ship | 3 | Ronnie Nash | Preston M. Burch | Brookmeade Stable | 1-1/8 | 1:50.80 | |
I need to know the count of rows and columns in this specific table. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_231
WTQ_204-csv_810.jpg
Regarding the table displayed, can you identify how many rows and columns it has? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> ZOOM | Cast Member 1 | Cast Member 2 | Cast Member 3 | Cast Member 4 | Cast Member 5 | Cast Member 6 | Cast Member 7 Season 1 (1999) | Zoe Costello | Jared Nathan | Keiko Yoshida | Pablo Velez, Jr. | Alisa Besher | David Toropov | Lynese Browder Season 2 (2000) | Raymond \Ray\" MacMore" | Caroline Botelho | Claudio Schwartz | Alisa Besher | Jessica \Jessie\" Ogungbadero" | Kenneth \Kenny\" Yates" | Zoe Costello Season 3 (2001) | Frances Domond | Kenneth \Kenny\" Yates" | Rachel Redd | Eric Rollins | Kaleigh Cronin | Kevin \Buzz\" Barrette" | Caroline Botelho Season 4 (2002) | Aline Toupi | Garrett DiBona | Rachel Redd | Matthew \Matt\" Runyon" | Estuardo Alvizures | Kaleigh Cronin | Caroline Botelho Season 5 (2003) | Caroline Botelho | Aline Toupi | Estuardo Alvizures | Garrett DiBona | Michael \Mike\" Hansen" | Kortney Sumner | Elena \Shing Ying\" Shieh" Season 6 (2004) | Michael \Mike\" Hansen" | Kortney Sumner | Francesco Tena | Cara Harvey | Kyle Larrow | Maya Morales | Elena \Shing Ying\" Shieh" Season 7 (2005) | W. Nick Henry | Taylor Garron | Francesco Tena | Noreen Raja | Emily Marshall | Kyle Larrow | Elena \Shing Ying\" Shieh"
WTQ_for_TSD
ZOOM | Cast Member 1 | Cast Member 2 | Cast Member 3 | Cast Member 4 | Cast Member 5 | Cast Member 6 | Cast Member 7 Season 1 (1999) | Zoe Costello | Jared Nathan | Keiko Yoshida | Pablo Velez, Jr. | Alisa Besher | David Toropov | Lynese Browder Season 2 (2000) | Raymond \Ray\" MacMore" | Caroline Botelho | Claudio Schwartz | Alisa Besher | Jessica \Jessie\" Ogungbadero" | Kenneth \Kenny\" Yates" | Zoe Costello Season 3 (2001) | Frances Domond | Kenneth \Kenny\" Yates" | Rachel Redd | Eric Rollins | Kaleigh Cronin | Kevin \Buzz\" Barrette" | Caroline Botelho Season 4 (2002) | Aline Toupi | Garrett DiBona | Rachel Redd | Matthew \Matt\" Runyon" | Estuardo Alvizures | Kaleigh Cronin | Caroline Botelho Season 5 (2003) | Caroline Botelho | Aline Toupi | Estuardo Alvizures | Garrett DiBona | Michael \Mike\" Hansen" | Kortney Sumner | Elena \Shing Ying\" Shieh" Season 6 (2004) | Michael \Mike\" Hansen" | Kortney Sumner | Francesco Tena | Cara Harvey | Kyle Larrow | Maya Morales | Elena \Shing Ying\" Shieh" Season 7 (2005) | W. Nick Henry | Taylor Garron | Francesco Tena | Noreen Raja | Emily Marshall | Kyle Larrow | Elena \Shing Ying\" Shieh"
Regarding the table displayed, can you identify how many rows and columns it has? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_232
WTQ_203-csv_68.jpg
Please ascertain the quantity of rows and columns within the provided table. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Date | Time | | Score | | Set 1 | Set 2 | Set 3 | Set 4 | Set 5 | Total | Report 17 Nov | 14:00 | Canada | 3–0 | Kazakhstan | 25–21 | 26–24 | 25–21 | | | 76–66 | P2 P3 17 Nov | 16:00 | Russia | 0–3 | Serbia and Montenegro | 22–25 | 18–25 | 23–25 | | | 63–75 | P2 P3 17 Nov | 18:00 | Tunisia | 3–2 | South Korea | 25–22 | 24–26 | 17–25 | 28–26 | 15–13 | 109–112 | P2 P3 18 Nov | 14:00 | Russia | 3–0 | Tunisia | 25–15 | 29–27 | 25–20 | | | 79–62 | P2 P3 18 Nov | 16:00 | Serbia and Montenegro | 3–1 | Kazakhstan | 25–16 | 22–25 | 25–18 | 25–22 | | 97–81 | P2 P3 18 Nov | 18:10 | South Korea | 1–3 | Canada | 28–26 | 23–25 | 16–25 | 23–25 | | 90–101 | P2 P3 19 Nov | 14:00 | Kazakhstan | 1–3 | South Korea | 22–25 | 25–23 | 18–25 | 21–25 | | 86–98 | P2 P3 19 Nov | 16:15 | Tunisia | 0–3 | Serbia and Montenegro | 21–25 | 12–25 | 23–25 | | | 56–75 | P2 P3 19 Nov | 18:00 | Canada | 0–3 | Russia | 19–25 | 20–25 | 21–25 | | | 60–75 | P2 P3 21 Nov | 14:00 | Tunisia | 2–3 | Canada | 15–25 | 29–27 | 25–21 | 21–25 | 13–15 | 103–113 | P2 P3 21 Nov | 16:35 | Serbia and Montenegro | 3–1 | South Korea | 25–22 | 23–25 | 25–21 | 25–18 | | 98–86 | P2 P3 21 Nov | 18:50 | Russia | 3–0 | Kazakhstan | 25–16 | 25–18 | 25–18 | | | 75–52 | P2 P3 22 Nov | 14:00 | Kazakhstan | 0–3 | Tunisia | 19–25 | 23–25 | 24–26 | | | 66–76 | P2 P3 22 Nov | 16:00 | Canada | 0–3 | Serbia and Montenegro | 18–25 | 18–25 | 17–25 | | | 53–75 | P2 P3 22 Nov | 18:00 | South Korea | 0–3 | Russia | 13–25 | 21–25 | 13–25 | | | 47–75 | P2 P3
WTQ_for_TSD
Date | Time | | Score | | Set 1 | Set 2 | Set 3 | Set 4 | Set 5 | Total | Report 17 Nov | 14:00 | Canada | 3–0 | Kazakhstan | 25–21 | 26–24 | 25–21 | | | 76–66 | P2 P3 17 Nov | 16:00 | Russia | 0–3 | Serbia and Montenegro | 22–25 | 18–25 | 23–25 | | | 63–75 | P2 P3 17 Nov | 18:00 | Tunisia | 3–2 | South Korea | 25–22 | 24–26 | 17–25 | 28–26 | 15–13 | 109–112 | P2 P3 18 Nov | 14:00 | Russia | 3–0 | Tunisia | 25–15 | 29–27 | 25–20 | | | 79–62 | P2 P3 18 Nov | 16:00 | Serbia and Montenegro | 3–1 | Kazakhstan | 25–16 | 22–25 | 25–18 | 25–22 | | 97–81 | P2 P3 18 Nov | 18:10 | South Korea | 1–3 | Canada | 28–26 | 23–25 | 16–25 | 23–25 | | 90–101 | P2 P3 19 Nov | 14:00 | Kazakhstan | 1–3 | South Korea | 22–25 | 25–23 | 18–25 | 21–25 | | 86–98 | P2 P3 19 Nov | 16:15 | Tunisia | 0–3 | Serbia and Montenegro | 21–25 | 12–25 | 23–25 | | | 56–75 | P2 P3 19 Nov | 18:00 | Canada | 0–3 | Russia | 19–25 | 20–25 | 21–25 | | | 60–75 | P2 P3 21 Nov | 14:00 | Tunisia | 2–3 | Canada | 15–25 | 29–27 | 25–21 | 21–25 | 13–15 | 103–113 | P2 P3 21 Nov | 16:35 | Serbia and Montenegro | 3–1 | South Korea | 25–22 | 23–25 | 25–21 | 25–18 | | 98–86 | P2 P3 21 Nov | 18:50 | Russia | 3–0 | Kazakhstan | 25–16 | 25–18 | 25–18 | | | 75–52 | P2 P3 22 Nov | 14:00 | Kazakhstan | 0–3 | Tunisia | 19–25 | 23–25 | 24–26 | | | 66–76 | P2 P3 22 Nov | 16:00 | Canada | 0–3 | Serbia and Montenegro | 18–25 | 18–25 | 17–25 | | | 53–75 | P2 P3 22 Nov | 18:00 | South Korea | 0–3 | Russia | 13–25 | 21–25 | 13–25 | | | 47–75 | P2 P3
Please ascertain the quantity of rows and columns within the provided table. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_233
WTQ_204-csv_934.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> Rank | Pair | Country | Athletes | Time | Deficit | 3 | Netherlands | Sven Kramer Koen Verweij Jan Blokhuijsen | 3:41.43 | | 4 | United States | Shani Davis Brian Hansen Jonathan Kuck | 3:43.42 | +1.99 | 2 | Russia | Ivan Skobrev Denis Yuskov Yevgeny Lalenkov | 3:43.62 | +2.19 4 | 1 | Canada | Denny Morrison Mathieu Giroux Lucas Makowsky | 3:44.38 | +2.95 5 | 1 | Norway | Sverre Lunde Pedersen Håvard Bøkko Kristian Reistad Fredriksen | 3:46.33 | +4.90 6 | 3 | Germany | Patrick Beckert Marco Weber Robert Lehmann | 3:46.48 | +5.05 7 | 4 | South Korea | Lee Seung-hoon Joo Hyong-jun Ko Byung-wook | 3:47.18 | +5.75 8 | 2 | Poland | Zbigniew Bródka Konrad Niedźwiedzki Jan Szymański | 3:47.72 | +6.29
WTQ_for_TSD
Rank | Pair | Country | Athletes | Time | Deficit | 3 | Netherlands | Sven Kramer Koen Verweij Jan Blokhuijsen | 3:41.43 | | 4 | United States | Shani Davis Brian Hansen Jonathan Kuck | 3:43.42 | +1.99 | 2 | Russia | Ivan Skobrev Denis Yuskov Yevgeny Lalenkov | 3:43.62 | +2.19 4 | 1 | Canada | Denny Morrison Mathieu Giroux Lucas Makowsky | 3:44.38 | +2.95 5 | 1 | Norway | Sverre Lunde Pedersen Håvard Bøkko Kristian Reistad Fredriksen | 3:46.33 | +4.90 6 | 3 | Germany | Patrick Beckert Marco Weber Robert Lehmann | 3:46.48 | +5.05 7 | 4 | South Korea | Lee Seung-hoon Joo Hyong-jun Ko Byung-wook | 3:47.18 | +5.75 8 | 2 | Poland | Zbigniew Bródka Konrad Niedźwiedzki Jan Szymański | 3:47.72 | +6.29
For the table shown in this image, can you tell me the row and column numbers of this table? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_234
WTQ_204-csv_404.jpg
Could you calculate the row number and column number in this table? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Week | Date | Opponent | Results Final score | Results Team record | Venue | Attendance 1 | September 18 | Washington Redskins | L 24–21 | 0–1 | Metropolitan Stadium | 47,900 2 | September 24 | at Detroit Lions | W 34–10 | 1–1 | Tiger Stadium | 54,418 3 | October 1 | Miami Dolphins | L 16–14 | 1–2 | Metropolitan Stadium | 47,900 4 | October 8 | St. Louis Cardinals | L 19–17 | 1–3 | Metropolitan Stadium | 49,687 5 | October 15 | at Denver Broncos | W 23–20 | 2–3 | Mile High Stadium | 51,656 6 | October 23 | at Chicago Bears | L 13–10 | 2–4 | Soldier Field | 55,701 7 | October 29 | at Green Bay Packers | W 27–13 | 3–4 | Lambeau Field | 56,263 8 | November 5 | New Orleans Saints | W 37–6 | 4–4 | Metropolitan Stadium | 49,784 9 | November 12 | Detroit Lions | W 16–14 | 5–4 | Metropolitan Stadium | 49,784 10 | November 19 | at Los Angeles Rams | W 45–41 | 6–4 | Los Angeles Memorial Coliseum | 77,982 11 | November 26 | at Pittsburgh Steelers | L 23–10 | 6–5 | Three Rivers Stadium | 50,348 12 | December 3 | Chicago Bears | W 23–10 | 7–5 | Metropolitan Stadium | 49,784 13 | December 10 | Green Bay Packers | L 23–7 | 7–6 | Metropolitan Stadium | 49,784 14 | December 16 | at San Francisco 49ers | L 20–17 | 7–7 | Candlestick Park | 61,214
WTQ_for_TSD
Week | Date | Opponent | Results Final score | Results Team record | Venue | Attendance 1 | September 18 | Washington Redskins | L 24–21 | 0–1 | Metropolitan Stadium | 47,900 2 | September 24 | at Detroit Lions | W 34–10 | 1–1 | Tiger Stadium | 54,418 3 | October 1 | Miami Dolphins | L 16–14 | 1–2 | Metropolitan Stadium | 47,900 4 | October 8 | St. Louis Cardinals | L 19–17 | 1–3 | Metropolitan Stadium | 49,687 5 | October 15 | at Denver Broncos | W 23–20 | 2–3 | Mile High Stadium | 51,656 6 | October 23 | at Chicago Bears | L 13–10 | 2–4 | Soldier Field | 55,701 7 | October 29 | at Green Bay Packers | W 27–13 | 3–4 | Lambeau Field | 56,263 8 | November 5 | New Orleans Saints | W 37–6 | 4–4 | Metropolitan Stadium | 49,784 9 | November 12 | Detroit Lions | W 16–14 | 5–4 | Metropolitan Stadium | 49,784 10 | November 19 | at Los Angeles Rams | W 45–41 | 6–4 | Los Angeles Memorial Coliseum | 77,982 11 | November 26 | at Pittsburgh Steelers | L 23–10 | 6–5 | Three Rivers Stadium | 50,348 12 | December 3 | Chicago Bears | W 23–10 | 7–5 | Metropolitan Stadium | 49,784 13 | December 10 | Green Bay Packers | L 23–7 | 7–6 | Metropolitan Stadium | 49,784 14 | December 16 | at San Francisco 49ers | L 20–17 | 7–7 | Candlestick Park | 61,214
Could you calculate the row number and column number in this table? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_235
WTQ_204-csv_773.jpg
Regarding the table displayed, can you identify how many rows and columns it has? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Team | City | Years active | Seasons played | Win–loss record | Win% | Playoffs appearances Anderson Packers | Anderson, Indiana | 1949–1950 | 1 | 37–27 | .578 | 1 BAA Buffalo | Buffalo, New York | Never Played | 0 | 0–0 | N/A | 0 BAA Indianapolis | Indianapolis, Indiana | Never Played | 0 | 0–0 | N/A | 0 Baltimore Bullets* | Baltimore, Maryland | 1947–1954 | 8 | 158–292 | .351 | 3 Chicago Stags | Chicago, Illinois | 1946–1950 | 4 | 145–92 | .612 | 4 Cleveland Rebels | Cleveland, Ohio | 1946–1947 | 1 | 30–30 | .500 | 1 Denver Nuggets | Denver, Colorado | 1949–1950 | 1 | 11–51 | .177 | 0 Detroit Falcons | Detroit, Michigan | 1946–1947 | 1 | 20–40 | .333 | 0 Indianapolis Jets | Indianapolis, Indiana | 1948–1949 | 1 | 18–42 | .300 | 0 Indianapolis Olympians | Indianapolis, Indiana | 1949–1953 | 4 | 132–137 | .491 | 4 Pittsburgh Ironmen | Pittsburgh, Pennsylvania | 1946–1947 | 1 | 15–45 | .250 | 0 Providence Steamrollers | Providence, Rhode Island | 1946–1949 | 3 | 46–122 | .274 | 0 Sheboygan Red Skins | Sheboygan, Wisconsin | 1949–1950 | 1 | 22–40 | .355 | 1 St. Louis Bombers | St. Louis, Missouri | 1946–1950 | 4 | 122–115 | .515 | 3 Toronto Huskies | Toronto, Ontario | 1946–1947 | 1 | 22–38 | .367 | 0 Washington Capitols | Washington, D.C. | 1946–1951 | 5 | 157–114 | .579 | 4 Waterloo Hawks | Waterloo, Iowa | 1949–1950 | 1 | 19–43 | .306 | 0
WTQ_for_TSD
Team | City | Years active | Seasons played | Win–loss record | Win% | Playoffs appearances Anderson Packers | Anderson, Indiana | 1949–1950 | 1 | 37–27 | .578 | 1 BAA Buffalo | Buffalo, New York | Never Played | 0 | 0–0 | N/A | 0 BAA Indianapolis | Indianapolis, Indiana | Never Played | 0 | 0–0 | N/A | 0 Baltimore Bullets* | Baltimore, Maryland | 1947–1954 | 8 | 158–292 | .351 | 3 Chicago Stags | Chicago, Illinois | 1946–1950 | 4 | 145–92 | .612 | 4 Cleveland Rebels | Cleveland, Ohio | 1946–1947 | 1 | 30–30 | .500 | 1 Denver Nuggets | Denver, Colorado | 1949–1950 | 1 | 11–51 | .177 | 0 Detroit Falcons | Detroit, Michigan | 1946–1947 | 1 | 20–40 | .333 | 0 Indianapolis Jets | Indianapolis, Indiana | 1948–1949 | 1 | 18–42 | .300 | 0 Indianapolis Olympians | Indianapolis, Indiana | 1949–1953 | 4 | 132–137 | .491 | 4 Pittsburgh Ironmen | Pittsburgh, Pennsylvania | 1946–1947 | 1 | 15–45 | .250 | 0 Providence Steamrollers | Providence, Rhode Island | 1946–1949 | 3 | 46–122 | .274 | 0 Sheboygan Red Skins | Sheboygan, Wisconsin | 1949–1950 | 1 | 22–40 | .355 | 1 St. Louis Bombers | St. Louis, Missouri | 1946–1950 | 4 | 122–115 | .515 | 3 Toronto Huskies | Toronto, Ontario | 1946–1947 | 1 | 22–38 | .367 | 0 Washington Capitols | Washington, D.C. | 1946–1951 | 5 | 157–114 | .579 | 4 Waterloo Hawks | Waterloo, Iowa | 1949–1950 | 1 | 19–43 | .306 | 0
Regarding the table displayed, can you identify how many rows and columns it has? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_236
WTQ_204-csv_674.jpg
Please determine the total count of rows and columns in the provided table, respectively. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> No. in season | No. in series | Title | Canadian airdate | US airdate | Production code 1–2 | 318–319 | \Summertime\"" | July 11, 2013 | July 11, 2013 | 1301 & 1302 3 | 320 | \All I Wanna Do\"" | July 18, 2013 | July 18, 2013 | 1303 4 | 321 | \My Own Worst Enemy\"" | July 25, 2013 | July 25, 2013 | 1304 5 | 322 | \About A Girl\"" | August 1, 2013 | August 1, 2013 | 1305 6 | 323 | \Cannonball\"" | August 8, 2013 | August 8, 2013 | 1306 7 | 324 | \Honey\"" | August 15, 2013 | August 15, 2013 | 1307 8 | 325 | \Young Forever\"" | August 22, 2013 | August 22, 2013 | 1308 9 | 326 | \This Is How We Do It\"" | October 3, 2013 | October 3, 2013 | 1309 10 | 327 | \You Got Me\"" | October 10, 2013 | October 10, 2013 | 1310 11 | 328 | \You Oughta Know\"" | October 17, 2013 | October 17, 2013 | 1311 12 | 329 | \Everything You've Done Wrong\"" | October 24, 2013 | October 24, 2013 | 1312 13 | 330 | \Who Do You Think You Are\"" | October 31, 2013 | October 31, 2013 | 1313 14 | 331 | \Barely Breathing\"" | November 7, 2013 | November 7, 2013 | 1314 15 | 332 | \Black Or White\"" | November 14, 2013 | November 14, 2013 | 1315 16 | 333 | \Spiderwebs\"" | November 21, 2013 | November 21, 2013 | 1316 17 | 334 | \The World I Know\"" | January 28, 2014 | January 28, 2014 | 1317 18 | 335 | \Better Man\"" | February 4, 2014 | February 4, 2014 | 1318 19 | 336 | \Dig Me Out\"" | February 11, 2014 | February 11, 2014 | 1319 20 | 337 | \Power to the People\"" | February 18, 2014 | February 18, 2014 | 1320 21 | 338 | \No Surprises\"" | February 25, 2014 | February 25, 2014 | 1321 22 | 339 | \Basket Case\"" | March 4, 2014 | March 4, 2014 | 1322 23–24 | 340–341 | \Unbelievable\"" | March 11, 2014 | March 11, 2014 | 1323 & 1324 25 | 342 | \What It's Like\"" | March 18, 2014 | March 18, 2014 | 1325 26 | 343 | \Close to Me\"" | March 25, 2014 | March 25, 2014 | 1326 27 | 344 | \Army of Me\"" | April 1, 2014 | April 1, 2014 | 1327 28 | 345 | \Everything Is Everything\"" | April 8, 2014 | April 8, 2014 | 1328 29 | 346 | \Sparks Will Fly\" Part One" | April 15, 2014 | April 15, 2014 | 1329 30 | 347 | \Sparks Will Fly\" Part Two" | April 22, 2014 | April 22, 2014 | 1330 31 | 348 | \You Are Not Alone\"" | June 3, 2014 | June 3, 2014 | 1331 32 | 349 | \Enjoy The Silence\"" | June 10, 2014 | June 10, 2014 | 1332 33 | 350 | \How Bizarre\"" | June 17, 2014 | June 17, 2014 | 1333 34 | 351 | \My Hero\"" | June 24, 2014 | June 24, 2014 | 1334 35 | 352 | \Hypnotize\"" | July 1, 2014 | July 1, 2014 | 1335 36 | 353 | \Out Of My Head\"" | July 8, 2014 | July 8, 2014 | 1336 37 | 354 | TBA | July 15, 2014 | July 15, 2014 | 1337 38 | 355 | TBA | July 22, 2014 | July 22, 2014 | 1338 39 | 356 | \Thunderstruck\" Part One" | July 29, 2014 | July 29, 2014 | 1339 40 | 357 | \Thundestruck\" Part Two" | July 29, 2014 | July 29, 2014 | 1340
WTQ_for_TSD
No. in season | No. in series | Title | Canadian airdate | US airdate | Production code 1–2 | 318–319 | \Summertime\"" | July 11, 2013 | July 11, 2013 | 1301 & 1302 3 | 320 | \All I Wanna Do\"" | July 18, 2013 | July 18, 2013 | 1303 4 | 321 | \My Own Worst Enemy\"" | July 25, 2013 | July 25, 2013 | 1304 5 | 322 | \About A Girl\"" | August 1, 2013 | August 1, 2013 | 1305 6 | 323 | \Cannonball\"" | August 8, 2013 | August 8, 2013 | 1306 7 | 324 | \Honey\"" | August 15, 2013 | August 15, 2013 | 1307 8 | 325 | \Young Forever\"" | August 22, 2013 | August 22, 2013 | 1308 9 | 326 | \This Is How We Do It\"" | October 3, 2013 | October 3, 2013 | 1309 10 | 327 | \You Got Me\"" | October 10, 2013 | October 10, 2013 | 1310 11 | 328 | \You Oughta Know\"" | October 17, 2013 | October 17, 2013 | 1311 12 | 329 | \Everything You've Done Wrong\"" | October 24, 2013 | October 24, 2013 | 1312 13 | 330 | \Who Do You Think You Are\"" | October 31, 2013 | October 31, 2013 | 1313 14 | 331 | \Barely Breathing\"" | November 7, 2013 | November 7, 2013 | 1314 15 | 332 | \Black Or White\"" | November 14, 2013 | November 14, 2013 | 1315 16 | 333 | \Spiderwebs\"" | November 21, 2013 | November 21, 2013 | 1316 17 | 334 | \The World I Know\"" | January 28, 2014 | January 28, 2014 | 1317 18 | 335 | \Better Man\"" | February 4, 2014 | February 4, 2014 | 1318 19 | 336 | \Dig Me Out\"" | February 11, 2014 | February 11, 2014 | 1319 20 | 337 | \Power to the People\"" | February 18, 2014 | February 18, 2014 | 1320 21 | 338 | \No Surprises\"" | February 25, 2014 | February 25, 2014 | 1321 22 | 339 | \Basket Case\"" | March 4, 2014 | March 4, 2014 | 1322 23–24 | 340–341 | \Unbelievable\"" | March 11, 2014 | March 11, 2014 | 1323 & 1324 25 | 342 | \What It's Like\"" | March 18, 2014 | March 18, 2014 | 1325 26 | 343 | \Close to Me\"" | March 25, 2014 | March 25, 2014 | 1326 27 | 344 | \Army of Me\"" | April 1, 2014 | April 1, 2014 | 1327 28 | 345 | \Everything Is Everything\"" | April 8, 2014 | April 8, 2014 | 1328 29 | 346 | \Sparks Will Fly\" Part One" | April 15, 2014 | April 15, 2014 | 1329 30 | 347 | \Sparks Will Fly\" Part Two" | April 22, 2014 | April 22, 2014 | 1330 31 | 348 | \You Are Not Alone\"" | June 3, 2014 | June 3, 2014 | 1331 32 | 349 | \Enjoy The Silence\"" | June 10, 2014 | June 10, 2014 | 1332 33 | 350 | \How Bizarre\"" | June 17, 2014 | June 17, 2014 | 1333 34 | 351 | \My Hero\"" | June 24, 2014 | June 24, 2014 | 1334 35 | 352 | \Hypnotize\"" | July 1, 2014 | July 1, 2014 | 1335 36 | 353 | \Out Of My Head\"" | July 8, 2014 | July 8, 2014 | 1336 37 | 354 | TBA | July 15, 2014 | July 15, 2014 | 1337 38 | 355 | TBA | July 22, 2014 | July 22, 2014 | 1338 39 | 356 | \Thunderstruck\" Part One" | July 29, 2014 | July 29, 2014 | 1339 40 | 357 | \Thundestruck\" Part Two" | July 29, 2014 | July 29, 2014 | 1340
Please determine the total count of rows and columns in the provided table, respectively. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_237
WTQ_204-csv_348.jpg
Provide me with the row number and column number for the table shown in this image. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Year | Award | Category | Recipient | Result 2012 | Cyworld Digital Music Awards | Rookie & Song of the Month (February) | \Heaven\"" | Won 2012 | Asia Song Festival | New Artist Award | Herself | Won 2012 | 4th MelOn Music Awards | Best New Artist | Herself | Won 2012 | Soompi Gayo Awards | Top 50 Songs (#3) | \Heaven\"" | Won 2012 | So-Loved Awards | Best Female Newcomer | Herself | Won 2012 | 14th Mnet Asian Music Awards | Best New Female Artist | Herself | Won 2013 | 27th Golden Disk Awards | Best New Artist | Herself | Won 2013 | 23rd Seoul Music Awards | Rookie Award | Herself | Won 2013 | Mnet Pre-Grammy Awards | Mnet Rising Star | Herself | Won 2013 | 2nd Gaon Chart K-Pop Awards | New Female Solo Artist | Herself | Won 2013 | 5th MelOn Music Awards | Top 10 Artists | Herself | Won 2013 | 15th Mnet Asian Music Awards | Best Female Artist | Herself | Nominated 2013 | 15th Mnet Asian Music Awards | Artist of the Year | Herself | Nominated 2013 | 15th Mnet Asian Music Awards | Best Vocal Performance - Female | \U&I\"" | Won 2013 | 15th Mnet Asian Music Awards | BC - UnionPay Song of the year | \U&I\"" | Nominated 2014 | 28th Golden Disk Awards | Digital Bonsang | \U&I\"" | Won 2014 | Soompi Music Awards | Best Female Artist | \U&I\"" | Won
WTQ_for_TSD
Year | Award | Category | Recipient | Result 2012 | Cyworld Digital Music Awards | Rookie & Song of the Month (February) | \Heaven\"" | Won 2012 | Asia Song Festival | New Artist Award | Herself | Won 2012 | 4th MelOn Music Awards | Best New Artist | Herself | Won 2012 | Soompi Gayo Awards | Top 50 Songs (#3) | \Heaven\"" | Won 2012 | So-Loved Awards | Best Female Newcomer | Herself | Won 2012 | 14th Mnet Asian Music Awards | Best New Female Artist | Herself | Won 2013 | 27th Golden Disk Awards | Best New Artist | Herself | Won 2013 | 23rd Seoul Music Awards | Rookie Award | Herself | Won 2013 | Mnet Pre-Grammy Awards | Mnet Rising Star | Herself | Won 2013 | 2nd Gaon Chart K-Pop Awards | New Female Solo Artist | Herself | Won 2013 | 5th MelOn Music Awards | Top 10 Artists | Herself | Won 2013 | 15th Mnet Asian Music Awards | Best Female Artist | Herself | Nominated 2013 | 15th Mnet Asian Music Awards | Artist of the Year | Herself | Nominated 2013 | 15th Mnet Asian Music Awards | Best Vocal Performance - Female | \U&I\"" | Won 2013 | 15th Mnet Asian Music Awards | BC - UnionPay Song of the year | \U&I\"" | Nominated 2014 | 28th Golden Disk Awards | Digital Bonsang | \U&I\"" | Won 2014 | Soompi Music Awards | Best Female Artist | \U&I\"" | Won
Provide me with the row number and column number for the table shown in this image. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_238
WTQ_204-csv_657.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Date | Time | Opponent# | Rank# | Site | TV | Result | Attendance September 1 | 2:30 PM | #9 (FCS) Northern Iowa* | #12 | Camp Randall Stadium • Madison, WI | BTN | W 26–21 | 79,568 September 8 | 3:00 PM | at Oregon State* | #13 | Reser Stadium • Corvallis, OR | FX | L 7–10 | 42,189 September 15 | 7:00 PM | Utah State* | #22 | Camp Randall Stadium • Madison, WI | BTN | W 16–14 | 79,332 September 22 | 11:00 AM | UTEP* | #24 | Camp Randall Stadium • Madison, WI | ESPN2 | W 37–26 | 79,806 September 29 | 7:00 PM | at #20 Nebraska | #23 | Memorial Stadium • Lincoln, NE | ABC | L 27–30 | 85,962 October 6 | 2:30 PM | Illinois | | Camp Randall Stadium • Madison, WI | ABC/ESPN2 | W 31–14 | 80,096 October 13 | 11:00 AM | at Purdue | | Ross-Ade Stadium • West Lafayette, IN | BTN | W 38–14 | 46,007 October 20 | 11:00 AM | Minnesota | | Camp Randall Stadium • Madison, WI (Paul Bunyan's Axe) | ESPNU | W 38–13 | 80,587 October 27 | 2:30 PM | Michigan State | #25 | Camp Randall Stadium • Madison, WI | ABC/ESPN2 | L 13–16 OT | 80,538 November 10 | 11:00 AM | at Indiana | | Memorial Stadium • Bloomington, IN | ESPN2 | W 62–14 | 43,240 November 17 | 2:30 PM | Ohio State | | Camp Randall Stadium • Madison, WI | ABC/ESPN2 | L 14–21 OT | 80,112 November 24 | 2:30 PM | at Penn State | | Beaver Stadium • University Park, PA | ESPN2 | L 21–24 OT | 93,505 December 1 | 7:00 PM | vs. #14 Nebraska | | Lucas Oil Stadium • Indianapolis, IN (Big Ten Championship Game) | FOX | W 70–31 | 41,260 January 1, 2013 | 4:10 PM | vs. #8 Stanford | #23 | Rose Bowl • Pasadena, CA (Rose Bowl) | ESPN | L 14–20 | 93,259
WTQ_for_TSD
Date | Time | Opponent# | Rank# | Site | TV | Result | Attendance September 1 | 2:30 PM | #9 (FCS) Northern Iowa* | #12 | Camp Randall Stadium • Madison, WI | BTN | W 26–21 | 79,568 September 8 | 3:00 PM | at Oregon State* | #13 | Reser Stadium • Corvallis, OR | FX | L 7–10 | 42,189 September 15 | 7:00 PM | Utah State* | #22 | Camp Randall Stadium • Madison, WI | BTN | W 16–14 | 79,332 September 22 | 11:00 AM | UTEP* | #24 | Camp Randall Stadium • Madison, WI | ESPN2 | W 37–26 | 79,806 September 29 | 7:00 PM | at #20 Nebraska | #23 | Memorial Stadium • Lincoln, NE | ABC | L 27–30 | 85,962 October 6 | 2:30 PM | Illinois | | Camp Randall Stadium • Madison, WI | ABC/ESPN2 | W 31–14 | 80,096 October 13 | 11:00 AM | at Purdue | | Ross-Ade Stadium • West Lafayette, IN | BTN | W 38–14 | 46,007 October 20 | 11:00 AM | Minnesota | | Camp Randall Stadium • Madison, WI (Paul Bunyan's Axe) | ESPNU | W 38–13 | 80,587 October 27 | 2:30 PM | Michigan State | #25 | Camp Randall Stadium • Madison, WI | ABC/ESPN2 | L 13–16 OT | 80,538 November 10 | 11:00 AM | at Indiana | | Memorial Stadium • Bloomington, IN | ESPN2 | W 62–14 | 43,240 November 17 | 2:30 PM | Ohio State | | Camp Randall Stadium • Madison, WI | ABC/ESPN2 | L 14–21 OT | 80,112 November 24 | 2:30 PM | at Penn State | | Beaver Stadium • University Park, PA | ESPN2 | L 21–24 OT | 93,505 December 1 | 7:00 PM | vs. #14 Nebraska | | Lucas Oil Stadium • Indianapolis, IN (Big Ten Championship Game) | FOX | W 70–31 | 41,260 January 1, 2013 | 4:10 PM | vs. #8 Stanford | #23 | Rose Bowl • Pasadena, CA (Rose Bowl) | ESPN | L 14–20 | 93,259
For the table shown in this image, can you tell me the row and column numbers of this table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_239
WTQ_203-csv_514.jpg
I need to know the count of rows and columns in this specific table. Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Round | Round | Race | Date | Pole Position | Fastest Lap | Winning Club | Winning Team | Report 1 | R1 | Donington Park | August 31 | Beijing Guoan | Beijing Guoan | Beijing Guoan | Zakspeed | Report 1 | R2 | Donington Park | August 31 | | PSV Eindhoven | Sevilla FC | GTA Motor Competición | Report 2 | R1 | Nürburgring | September 21 | A.C. Milan | PSV Eindhoven | A.C. Milan | Scuderia Playteam | Report 2 | R2 | Nürburgring | September 21 | | SC Corinthians | PSV Eindhoven | Azerti Motorsport | Report 3 | R1 | Zolder | October 5 | Borussia Dortmund | Liverpool F.C. | Liverpool F.C. | Hitech Junior Team | Report 3 | R2 | Zolder | October 5 | | Atlético Madrid | Beijing Guoan | Zakspeed | Report 4 | R1 | Estoril | October 19 | A.S. Roma | Atlético Madrid | Liverpool F.C. | Hitech Junior Team | Report 4 | R2 | Estoril | October 19 | | Borussia Dortmund | Al Ain | Azerti Motorsport | Report 5 | R1 | Vallelunga | November 2 | Liverpool F.C. | Beijing Guoan | Beijing Guoan | Zakspeed | Report 5 | R2 | Vallelunga | November 2 | | Atlético Madrid | F.C. Porto | Hitech Junior Team | Report 6 | R1 | Jerez | November 23 | Liverpool F.C. | R.S.C. Anderlecht | A.C. Milan | Scuderia Playteam | Report 6 | R2 | Jerez | November 23 | | Beijing Guoan | Borussia Dortmund | Zakspeed | Report
WTQ_for_TSD
Round | Round | Race | Date | Pole Position | Fastest Lap | Winning Club | Winning Team | Report 1 | R1 | Donington Park | August 31 | Beijing Guoan | Beijing Guoan | Beijing Guoan | Zakspeed | Report 1 | R2 | Donington Park | August 31 | | PSV Eindhoven | Sevilla FC | GTA Motor Competición | Report 2 | R1 | Nürburgring | September 21 | A.C. Milan | PSV Eindhoven | A.C. Milan | Scuderia Playteam | Report 2 | R2 | Nürburgring | September 21 | | SC Corinthians | PSV Eindhoven | Azerti Motorsport | Report 3 | R1 | Zolder | October 5 | Borussia Dortmund | Liverpool F.C. | Liverpool F.C. | Hitech Junior Team | Report 3 | R2 | Zolder | October 5 | | Atlético Madrid | Beijing Guoan | Zakspeed | Report 4 | R1 | Estoril | October 19 | A.S. Roma | Atlético Madrid | Liverpool F.C. | Hitech Junior Team | Report 4 | R2 | Estoril | October 19 | | Borussia Dortmund | Al Ain | Azerti Motorsport | Report 5 | R1 | Vallelunga | November 2 | Liverpool F.C. | Beijing Guoan | Beijing Guoan | Zakspeed | Report 5 | R2 | Vallelunga | November 2 | | Atlético Madrid | F.C. Porto | Hitech Junior Team | Report 6 | R1 | Jerez | November 23 | Liverpool F.C. | R.S.C. Anderlecht | A.C. Milan | Scuderia Playteam | Report 6 | R2 | Jerez | November 23 | | Beijing Guoan | Borussia Dortmund | Zakspeed | Report
I need to know the count of rows and columns in this specific table. Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_240
WTQ_204-csv_645.jpg
Tell me the row and column numbers of the shown table. Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> Season | Team | Record | Head Coach | Quarterback | Leading Rusher | Leading Receiver | All-Pros | Runner Up 1970 | Dallas Cowboys | 10–4 | Tom Landry* | Craig Morton | Duane Thomas | Bob Hayes* | Howley | San Francisco 49ers 1971 | Dallas Cowboys† | 11–3 | Tom Landry* | Roger Staubach* | Duane Thomas | Bob Hayes* | Lilly*, Niland, Wright* | San Francisco 49ers 1972 | Washington Redskins | 11–3 | George Allen* | Billy Kilmer | Larry Brown | Charley Taylor* | Brown, Hanburger* | Dallas Cowboys 1973 | Minnesota Vikings | 12–2 | Bud Grant* | Fran Tarkenton* | Chuck Foreman | John Gilliam | Eller*, Page*, Yary* | Dallas Cowboys 1974 | Minnesota Vikings | 10–4 | Bud Grant* | Fran Tarkenton* | Chuck Foreman | Jim Lash | Page*, Yary* | Los Angeles Rams 1975 | Dallas Cowboys | 10–4 | Tom Landry* | Roger Staubach* | Robert Newhouse | Drew Pearson | none | Los Angeles Rams 1976 | Minnesota Vikings | 11–2–1 | Bud Grant* | Fran Tarkenton* | Chuck Foreman | Sammy White | Yary* | Los Angeles Rams 1977 | Dallas Cowboys† | 12–2 | Tom Landry* | Roger Staubach* | Tony Dorsett* | Drew Pearson | Harris, Herrera, Martin, Pearson | Minnesota Vikings 1978 | Dallas Cowboys | 12–4 | Tom Landry* | Roger Staubach* | Tony Dorsett* | Tony Hill | Harris, White* | Los Angeles Rams 1979 | Los Angeles Rams | 9–7 | Ray Malavasi | Pat Haden | Wendell Tyler | Preston Dennard | Brooks, Youngblood* | Tampa Bay Buccaneers 1980 | Philadelphia Eagles | 12–4 | Dick Vermeil | Ron Jaworski | Wilbert Montgomery | Charlie Smith | Johnson | Dallas Cowboys 1981 | San Francisco 49ers† | 13–3 | Bill Walsh* | Joe Montana* | Ricky Patton | Dwight Clark | Dean*, Lott* | Dallas Cowboys 1982 | Washington Redskins† | 8–1 | Joe Gibbs* | Joe Theismann | John Riggins* | Charlie Brown | Moseley | Dallas Cowboys 1983 | Washington Redskins | 14–2 | Joe Gibbs* | Joe Theismann | John Riggins* | Charlie Brown | Butz, Grimm*, Jacoby, Murphy, Nelms, Riggins*, Theismann | San Francisco 49ers 1984 | San Francisco 49ers† | 15–1 | Bill Walsh* | Joe Montana* | Wendell Tyler | Dwight Clark | Fahnhorst | Chicago Bears 1985 | Chicago Bears† | 15–1 | Mike Ditka* | Jim McMahon | Walter Payton* | Willie Gault | Covert, Dent*, McMichael, Payton*, Singletary* | Los Angeles Rams 1986 | New York Giants† | 14–2 | Bill Parcells* | Phil Simms | Joe Morris | Mark Bavaro | Bavaro, Landeta, Morris, Taylor* | Washington Redskins 1987 | Washington Redskins† | 11–4 | Joe Gibbs* | Jay Schroeder | George Rogers | Gary Clark | Clark, Wilburn | Minnesota Vikings 1988 | San Francisco 49ers† | 10–6 | Bill Walsh* | Joe Montana* | Roger Craig | Jerry Rice* | Craig, Rice* | Chicago Bears 1989 | San Francisco 49ers† | 14–2 | George Seifert | Joe Montana* | Roger Craig | Jerry Rice* | Cofer, Lott*, Montana*, Rice*, | Los Angeles Rams 1990 | New York Giants† | 13–3 | Bill Parcells* | Phil Simms | Ottis Anderson | Stephen Baker | Johnson, Landeta | San Francisco 49ers 1991 | Washington Redskins† | 14–2 | Joe Gibbs* | Mark Rypien | Earnest Byner | Gary Clark | Green*, Lachey | Detroit Lions 1992 | Dallas Cowboys† | 13–3 | Jimmy Johnson | Troy Aikman* | Emmitt Smith* | Michael Irvin* | Novacek, Smith* | San Francisco 49ers 1993 | Dallas Cowboys† | 12–4 | Jimmy Johnson | Troy Aikman* | Emmitt Smith* | Michael Irvin* | Smith*, Williams | San Francisco 49ers 1994 | San Francisco 49ers† | 13–3 | George Seifert | Steve Young* | Ricky Watters | Jerry Rice* | Rice*, Sanders*, Young* | Dallas Cowboys 1995 | Dallas Cowboys† | 12–4 | Barry Switzer | Troy Aikman* | Emmitt Smith* | Michael Irvin* | Newton, Smith*, Woodson | Green Bay Packers 1996 | Green Bay Packers† | 13–3 | Mike Holmgren | Brett Favre | Edgar Bennett | Antonio Freeman | Butler, Favre | Carolina Panthers 1997 | Green Bay Packers | 13–3 | Mike Holmgren | Brett Favre | Dorsey Levens | Antonio Freeman | Butler, Favre | San Francisco 49ers 1998 | Atlanta Falcons | 14–2 | Dan Reeves | Chris Chandler | Jamal Anderson | Tony Martin | Anderson | Minnesota Vikings 1999 | St. Louis Rams† | 13–3 | Dick Vermeil | Kurt Warner | Marshall Faulk* | Isaac Bruce | Carter, Faulk*, Pace, Warner | Tampa Bay Buccaneers 2000 | New York Giants | 12–4 | Jim Fassel | Kerry Collins | Tiki Barber | Amani Toomer | none | Minnesota Vikings 2001 | St. Louis Rams | 14–2 | Mike Martz | Kurt Warner | Marshall Faulk* | Torry Holt | Faulk*, Pace, Warner, Williams* | Philadelphia Eagles 2002 | Tampa Bay Buccaneers† | 12–4 | Jon Gruden | Brad Johnson | Michael Pittman | Keyshawn Johnson | Brooks*, Rice, Sapp* | Philadelphia Eagles 2003 | Carolina Panthers | 11–5 | John Fox | Jake Delhomme | Stephen Davis | Steve Smith | Jenkins | Philadelphia Eagles 2004 | Philadelphia Eagles | 13–3 | Andy Reid | Donovan McNabb | Brian Westbrook | Terrell Owens | Dawkins, Owens, Sheppard | Atlanta Falcons 2005 | Seattle Seahawks | 13–3 | Mike Holmgren | Matt Hasselbeck | Shaun Alexander | Bobby Engram | Alexander, Hutchinson, Jones*, Strong | Carolina Panthers 2006 | Chicago Bears | 13–3 | Lovie Smith | Rex Grossman | Thomas Jones | Muhsin Muhammad | Gould, Hester, Kreutz, Urlacher | New Orleans Saints 2007 | New York Giants† | 10–6 | Tom Coughlin | Eli Manning | Brandon Jacobs | Plaxico Burress | none | Green Bay Packers 2008 | Arizona Cardinals | 9–7 | Ken Whisenhunt | Kurt Warner | Edgerrin James | Larry Fitzgerald | Fitzgerald | Philadelphia Eagles 2009 | New Orleans Saints† | 13–3 | Sean Payton | Drew Brees | Pierre Thomas | Marques Colston | Evans | Minnesota Vikings 2010 | Green Bay Packers† | 10–6 | Mike McCarthy | Aaron Rodgers | Brandon Jackson | Greg Jennings | Clifton, Collins, Jennings, Matthews, Woodson | Chicago Bears 2011 | New York Giants† | 9–7 | Tom Coughlin | Eli Manning | Ahmad Bradshaw | Victor Cruz | Pierre-Paul | San Francisco 49ers 2012 | San Francisco 49ers | 11–4–1 | Jim Harbaugh | Colin Kaepernick | Frank Gore | Michael Crabtree | Bowman, Goldson, Iupati, Lee, Smith, Willis | Atlanta Falcons 2013 | Seattle Seahawks† | 13–3 | Pete Carroll | Russell Wilson | Marshawn Lynch | Golden Tate | Sherman, Thomas | San Francisco 49ers
WTQ_for_TSD
Season | Team | Record | Head Coach | Quarterback | Leading Rusher | Leading Receiver | All-Pros | Runner Up 1970 | Dallas Cowboys | 10–4 | Tom Landry* | Craig Morton | Duane Thomas | Bob Hayes* | Howley | San Francisco 49ers 1971 | Dallas Cowboys† | 11–3 | Tom Landry* | Roger Staubach* | Duane Thomas | Bob Hayes* | Lilly*, Niland, Wright* | San Francisco 49ers 1972 | Washington Redskins | 11–3 | George Allen* | Billy Kilmer | Larry Brown | Charley Taylor* | Brown, Hanburger* | Dallas Cowboys 1973 | Minnesota Vikings | 12–2 | Bud Grant* | Fran Tarkenton* | Chuck Foreman | John Gilliam | Eller*, Page*, Yary* | Dallas Cowboys 1974 | Minnesota Vikings | 10–4 | Bud Grant* | Fran Tarkenton* | Chuck Foreman | Jim Lash | Page*, Yary* | Los Angeles Rams 1975 | Dallas Cowboys | 10–4 | Tom Landry* | Roger Staubach* | Robert Newhouse | Drew Pearson | none | Los Angeles Rams 1976 | Minnesota Vikings | 11–2–1 | Bud Grant* | Fran Tarkenton* | Chuck Foreman | Sammy White | Yary* | Los Angeles Rams 1977 | Dallas Cowboys† | 12–2 | Tom Landry* | Roger Staubach* | Tony Dorsett* | Drew Pearson | Harris, Herrera, Martin, Pearson | Minnesota Vikings 1978 | Dallas Cowboys | 12–4 | Tom Landry* | Roger Staubach* | Tony Dorsett* | Tony Hill | Harris, White* | Los Angeles Rams 1979 | Los Angeles Rams | 9–7 | Ray Malavasi | Pat Haden | Wendell Tyler | Preston Dennard | Brooks, Youngblood* | Tampa Bay Buccaneers 1980 | Philadelphia Eagles | 12–4 | Dick Vermeil | Ron Jaworski | Wilbert Montgomery | Charlie Smith | Johnson | Dallas Cowboys 1981 | San Francisco 49ers† | 13–3 | Bill Walsh* | Joe Montana* | Ricky Patton | Dwight Clark | Dean*, Lott* | Dallas Cowboys 1982 | Washington Redskins† | 8–1 | Joe Gibbs* | Joe Theismann | John Riggins* | Charlie Brown | Moseley | Dallas Cowboys 1983 | Washington Redskins | 14–2 | Joe Gibbs* | Joe Theismann | John Riggins* | Charlie Brown | Butz, Grimm*, Jacoby, Murphy, Nelms, Riggins*, Theismann | San Francisco 49ers 1984 | San Francisco 49ers† | 15–1 | Bill Walsh* | Joe Montana* | Wendell Tyler | Dwight Clark | Fahnhorst | Chicago Bears 1985 | Chicago Bears† | 15–1 | Mike Ditka* | Jim McMahon | Walter Payton* | Willie Gault | Covert, Dent*, McMichael, Payton*, Singletary* | Los Angeles Rams 1986 | New York Giants† | 14–2 | Bill Parcells* | Phil Simms | Joe Morris | Mark Bavaro | Bavaro, Landeta, Morris, Taylor* | Washington Redskins 1987 | Washington Redskins† | 11–4 | Joe Gibbs* | Jay Schroeder | George Rogers | Gary Clark | Clark, Wilburn | Minnesota Vikings 1988 | San Francisco 49ers† | 10–6 | Bill Walsh* | Joe Montana* | Roger Craig | Jerry Rice* | Craig, Rice* | Chicago Bears 1989 | San Francisco 49ers† | 14–2 | George Seifert | Joe Montana* | Roger Craig | Jerry Rice* | Cofer, Lott*, Montana*, Rice*, | Los Angeles Rams 1990 | New York Giants† | 13–3 | Bill Parcells* | Phil Simms | Ottis Anderson | Stephen Baker | Johnson, Landeta | San Francisco 49ers 1991 | Washington Redskins† | 14–2 | Joe Gibbs* | Mark Rypien | Earnest Byner | Gary Clark | Green*, Lachey | Detroit Lions 1992 | Dallas Cowboys† | 13–3 | Jimmy Johnson | Troy Aikman* | Emmitt Smith* | Michael Irvin* | Novacek, Smith* | San Francisco 49ers 1993 | Dallas Cowboys† | 12–4 | Jimmy Johnson | Troy Aikman* | Emmitt Smith* | Michael Irvin* | Smith*, Williams | San Francisco 49ers 1994 | San Francisco 49ers† | 13–3 | George Seifert | Steve Young* | Ricky Watters | Jerry Rice* | Rice*, Sanders*, Young* | Dallas Cowboys 1995 | Dallas Cowboys† | 12–4 | Barry Switzer | Troy Aikman* | Emmitt Smith* | Michael Irvin* | Newton, Smith*, Woodson | Green Bay Packers 1996 | Green Bay Packers† | 13–3 | Mike Holmgren | Brett Favre | Edgar Bennett | Antonio Freeman | Butler, Favre | Carolina Panthers 1997 | Green Bay Packers | 13–3 | Mike Holmgren | Brett Favre | Dorsey Levens | Antonio Freeman | Butler, Favre | San Francisco 49ers 1998 | Atlanta Falcons | 14–2 | Dan Reeves | Chris Chandler | Jamal Anderson | Tony Martin | Anderson | Minnesota Vikings 1999 | St. Louis Rams† | 13–3 | Dick Vermeil | Kurt Warner | Marshall Faulk* | Isaac Bruce | Carter, Faulk*, Pace, Warner | Tampa Bay Buccaneers 2000 | New York Giants | 12–4 | Jim Fassel | Kerry Collins | Tiki Barber | Amani Toomer | none | Minnesota Vikings 2001 | St. Louis Rams | 14–2 | Mike Martz | Kurt Warner | Marshall Faulk* | Torry Holt | Faulk*, Pace, Warner, Williams* | Philadelphia Eagles 2002 | Tampa Bay Buccaneers† | 12–4 | Jon Gruden | Brad Johnson | Michael Pittman | Keyshawn Johnson | Brooks*, Rice, Sapp* | Philadelphia Eagles 2003 | Carolina Panthers | 11–5 | John Fox | Jake Delhomme | Stephen Davis | Steve Smith | Jenkins | Philadelphia Eagles 2004 | Philadelphia Eagles | 13–3 | Andy Reid | Donovan McNabb | Brian Westbrook | Terrell Owens | Dawkins, Owens, Sheppard | Atlanta Falcons 2005 | Seattle Seahawks | 13–3 | Mike Holmgren | Matt Hasselbeck | Shaun Alexander | Bobby Engram | Alexander, Hutchinson, Jones*, Strong | Carolina Panthers 2006 | Chicago Bears | 13–3 | Lovie Smith | Rex Grossman | Thomas Jones | Muhsin Muhammad | Gould, Hester, Kreutz, Urlacher | New Orleans Saints 2007 | New York Giants† | 10–6 | Tom Coughlin | Eli Manning | Brandon Jacobs | Plaxico Burress | none | Green Bay Packers 2008 | Arizona Cardinals | 9–7 | Ken Whisenhunt | Kurt Warner | Edgerrin James | Larry Fitzgerald | Fitzgerald | Philadelphia Eagles 2009 | New Orleans Saints† | 13–3 | Sean Payton | Drew Brees | Pierre Thomas | Marques Colston | Evans | Minnesota Vikings 2010 | Green Bay Packers† | 10–6 | Mike McCarthy | Aaron Rodgers | Brandon Jackson | Greg Jennings | Clifton, Collins, Jennings, Matthews, Woodson | Chicago Bears 2011 | New York Giants† | 9–7 | Tom Coughlin | Eli Manning | Ahmad Bradshaw | Victor Cruz | Pierre-Paul | San Francisco 49ers 2012 | San Francisco 49ers | 11–4–1 | Jim Harbaugh | Colin Kaepernick | Frank Gore | Michael Crabtree | Bowman, Goldson, Iupati, Lee, Smith, Willis | Atlanta Falcons 2013 | Seattle Seahawks† | 13–3 | Pete Carroll | Russell Wilson | Marshawn Lynch | Golden Tate | Sherman, Thomas | San Francisco 49ers
Tell me the row and column numbers of the shown table. Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_241
WTQ_203-csv_776.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> Season | Competition | Round | Club | Home | Away 1985–86 | UEFA Cup Winners' Cup | 1R | HJK Helsinki | 1–2 | 2–3 1986–87 | UEFA Cup | 1R | FC Barcelona | 1–1 | 0–0 1987–88 | UEFA Cup | 1R | FK Partizan Beograd | 2–0 | 1–2 1987–88 | UEFA Cup | 2R | Wismut Aue | 2–0 | 0–1 1987–88 | UEFA Cup | 1/16 | FC Barcelona | 1–0 | 1–4 1988–89 | UEFA Cup Winners' Cup | 1R | Lech Poznań | 2–3 | 0–1 1990–91 | UEFA Cup Winners' Cup | 1R | Olympiacos Piraeus | 0–2 | 1–3 1991–92 | UEFA European Cup | 1R | IFK Göteborg | 1–1 | 0–0 1996–97 | UEFA Cup Winners' Cup | QR | Humenné | 0–2 | 0–1 2009–10 | UEFA Europa League | 2QR | Motherwell | 1–0 | 1–8 2011–12 | UEFA Europa League | 1QR | FK Budućnost | 1–2 | 3–1 | | 2QR | FK Jablonec 97 | 0–2 | 1–5 2012–13 | UEFA Europa League | 1QR | Budapest Honvéd | 0–1 | 0–2
WTQ_for_TSD
Season | Competition | Round | Club | Home | Away 1985–86 | UEFA Cup Winners' Cup | 1R | HJK Helsinki | 1–2 | 2–3 1986–87 | UEFA Cup | 1R | FC Barcelona | 1–1 | 0–0 1987–88 | UEFA Cup | 1R | FK Partizan Beograd | 2–0 | 1–2 1987–88 | UEFA Cup | 2R | Wismut Aue | 2–0 | 0–1 1987–88 | UEFA Cup | 1/16 | FC Barcelona | 1–0 | 1–4 1988–89 | UEFA Cup Winners' Cup | 1R | Lech Poznań | 2–3 | 0–1 1990–91 | UEFA Cup Winners' Cup | 1R | Olympiacos Piraeus | 0–2 | 1–3 1991–92 | UEFA European Cup | 1R | IFK Göteborg | 1–1 | 0–0 1996–97 | UEFA Cup Winners' Cup | QR | Humenné | 0–2 | 0–1 2009–10 | UEFA Europa League | 2QR | Motherwell | 1–0 | 1–8 2011–12 | UEFA Europa League | 1QR | FK Budućnost | 1–2 | 3–1 | | 2QR | FK Jablonec 97 | 0–2 | 1–5 2012–13 | UEFA Europa League | 1QR | Budapest Honvéd | 0–1 | 0–2
This is a table picture. Can you figure out the row and column numbers for this particular table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_242
WTQ_202-csv_186.jpg
Provide me with the row number and column number for the table shown in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Vessel | Captor | Date | Location Porpoise | Raritan | 23 January 1845 | Rio de Janeiro Albert | Bainbridge | June 1845 | Bahia Laurens | Onkahye | 23 January 1848 | Rio de Janeiro A.D. Richardson | Perry | 11 December 1848 | Rio de Janeiro Independence | Perry | 13 December 1848 | Rio de Janeiro Susan | Perry | 6 February 1849 | Rio de Janeiro
WTQ_for_TSD
Vessel | Captor | Date | Location Porpoise | Raritan | 23 January 1845 | Rio de Janeiro Albert | Bainbridge | June 1845 | Bahia Laurens | Onkahye | 23 January 1848 | Rio de Janeiro A.D. Richardson | Perry | 11 December 1848 | Rio de Janeiro Independence | Perry | 13 December 1848 | Rio de Janeiro Susan | Perry | 6 February 1849 | Rio de Janeiro
Provide me with the row number and column number for the table shown in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_243
WTQ_204-csv_447.jpg
This image depicts a table. How many rows and columns does this table have? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> No. | Date | Tournament | Surface | Partnering | Opponent in the final | Score 1. | September 13, 2010 | Ecuador F2 | Hard | Roberto Quiroz | Peter Aarts Christopher Racz | 6–4, 6–4 2. | April 4, 2011 | Chile F2 | Clay | Sergio Galdós | Guillermo Hormazábal Rodrigo Pérez | 5–7, 7–6(5), [10–5] 3. | April 11, 2011 | Chile F3 | Clay | Roberto Quiroz | Luis David Martínez Miguel Ángel Reyes-Varela | 6–4, 7–5 4. | August 8, 2011 | Peru F1 | Clay | Sergio Galdós | Martín Cuevas Guido Pella | 6–4, 6–0 5. | August 5, 2012 | Manta | Hard | Renzo Olivo | Víctor Estrella João Souza | 6–3, 6–0 6. | August 20, 2012 | Colombia F2 | Clay | Ariel Behar | Nicolas Barrientos Michael Quintero | 2-1 Ret. 7. | August 26, 2012 | Ecuador F3 | Clay | Sergio Galdós | Mauricio Echazú Guillermo Rivera-Aránguiz | 6-2, 6-1 8. | October 8, 2012 | Chile F8 | Clay | Gustavo Sterin | Cristóbal Saavedra-Corvalán Guillermo Rivera-Aránguiz | 6-4, 7-5 9. | May 13, 2013 | Argentina F6 | Clay | Sergio Galdós | Franco Agamenone Jose Angel Carrizo | 4-6, 6-4, [10–1] 10. | May 27, 2013 | Argentina F8 | Clay | Sergio Galdós | Daniel Dutra da Silva Pablo Galdón | 6-0, 7-5
WTQ_for_TSD
No. | Date | Tournament | Surface | Partnering | Opponent in the final | Score 1. | September 13, 2010 | Ecuador F2 | Hard | Roberto Quiroz | Peter Aarts Christopher Racz | 6–4, 6–4 2. | April 4, 2011 | Chile F2 | Clay | Sergio Galdós | Guillermo Hormazábal Rodrigo Pérez | 5–7, 7–6(5), [10–5] 3. | April 11, 2011 | Chile F3 | Clay | Roberto Quiroz | Luis David Martínez Miguel Ángel Reyes-Varela | 6–4, 7–5 4. | August 8, 2011 | Peru F1 | Clay | Sergio Galdós | Martín Cuevas Guido Pella | 6–4, 6–0 5. | August 5, 2012 | Manta | Hard | Renzo Olivo | Víctor Estrella João Souza | 6–3, 6–0 6. | August 20, 2012 | Colombia F2 | Clay | Ariel Behar | Nicolas Barrientos Michael Quintero | 2-1 Ret. 7. | August 26, 2012 | Ecuador F3 | Clay | Sergio Galdós | Mauricio Echazú Guillermo Rivera-Aránguiz | 6-2, 6-1 8. | October 8, 2012 | Chile F8 | Clay | Gustavo Sterin | Cristóbal Saavedra-Corvalán Guillermo Rivera-Aránguiz | 6-4, 7-5 9. | May 13, 2013 | Argentina F6 | Clay | Sergio Galdós | Franco Agamenone Jose Angel Carrizo | 4-6, 6-4, [10–1] 10. | May 27, 2013 | Argentina F8 | Clay | Sergio Galdós | Daniel Dutra da Silva Pablo Galdón | 6-0, 7-5
This image depicts a table. How many rows and columns does this table have? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_244
WTQ_204-csv_2.jpg
How many rows and columns does the given table have? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> # | Massif | Region | Type of nature reserve | Preserved area | Buffer zone 1 | Chornohora | Zakarpattia | Carpathian Biosphere Reserve | 2476.8 ha | 12925 ha 2 | Uholka / Wide Meadow | Zakarpattia | Carpathian Biosphere Reserve | 11860 ha | 3301 ha 3 | Svydovets | Zakarpattia | Carpathian Biosphere Reserve | 3030.5 ha | 5639.5 ha 4 | Maramoros | Zakarpattia | Carpathian Biosphere Reserve | 2243.6 ha | 6230.4 ha 5 | Kuziy / Trybushany | Zakarpattia | Carpathian Biosphere Reserve | 1369.6 ha | 3163.4 ha 6 | Stuzhytsia / Uzhok | Zakarpattia | Uzh National Nature Park | 2532 ha | 3615 ha 7 | Stužica / Bukovské vrchy | Presov | Poloniny National Park | 2950 ha | 11300 ha 8 | Rožok | Presov | Presov Preserved areas | 67.1 ha | 41.4 ha 9 | Vihorlat | Presov | Presov Preserved areas | 2578 ha | 2413 ha 10 | Havešová | Presov | Presov Preserved areas | 171.3 ha | 63.9 ha 11 | Jasmund | Mecklenburg-Vorpommern | Jasmund National Park | 492.5 ha | 2510.5 ha 12 | Serrahn | Mecklenburg-Vorpommern | Müritz National Park | 268.1 ha | 2568 ha 13 | Grumsiner Forest | Brandenburg | Grumsiner Forest Nature Reserve | 590.1 ha | 274.3 ha 14 | Hainich | Thuringia | Hainich National Park | 1573.4 ha | 4085.4 ha 15 | Kellerwald | Hesse | Kellerwald-Edersee National Park | 1467.1 ha | 4271.4 ha
WTQ_for_TSD
# | Massif | Region | Type of nature reserve | Preserved area | Buffer zone 1 | Chornohora | Zakarpattia | Carpathian Biosphere Reserve | 2476.8 ha | 12925 ha 2 | Uholka / Wide Meadow | Zakarpattia | Carpathian Biosphere Reserve | 11860 ha | 3301 ha 3 | Svydovets | Zakarpattia | Carpathian Biosphere Reserve | 3030.5 ha | 5639.5 ha 4 | Maramoros | Zakarpattia | Carpathian Biosphere Reserve | 2243.6 ha | 6230.4 ha 5 | Kuziy / Trybushany | Zakarpattia | Carpathian Biosphere Reserve | 1369.6 ha | 3163.4 ha 6 | Stuzhytsia / Uzhok | Zakarpattia | Uzh National Nature Park | 2532 ha | 3615 ha 7 | Stužica / Bukovské vrchy | Presov | Poloniny National Park | 2950 ha | 11300 ha 8 | Rožok | Presov | Presov Preserved areas | 67.1 ha | 41.4 ha 9 | Vihorlat | Presov | Presov Preserved areas | 2578 ha | 2413 ha 10 | Havešová | Presov | Presov Preserved areas | 171.3 ha | 63.9 ha 11 | Jasmund | Mecklenburg-Vorpommern | Jasmund National Park | 492.5 ha | 2510.5 ha 12 | Serrahn | Mecklenburg-Vorpommern | Müritz National Park | 268.1 ha | 2568 ha 13 | Grumsiner Forest | Brandenburg | Grumsiner Forest Nature Reserve | 590.1 ha | 274.3 ha 14 | Hainich | Thuringia | Hainich National Park | 1573.4 ha | 4085.4 ha 15 | Kellerwald | Hesse | Kellerwald-Edersee National Park | 1467.1 ha | 4271.4 ha
How many rows and columns does the given table have? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_245
WTQ_203-csv_604.jpg
Please ascertain the quantity of rows and columns within the provided table. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Callsign | Area served | Frequency | Band | Fate | Freq currently | Purpose 7CAE | Hobart | 092.1 | FM | Changed call to 7THE ca. 1980 | 7THE | Community 7DY | Derby | | AM | Moved to Scottsdale and changed call to 7SD in 1954 | 7SD | Commercial 7EX | Launceston | 1008 | AM | Moved to FM in 2008 as 7EXX | silent | Commercial 7HO | Hobart | 0864 | AM | Moved to FM in 1990 as 7HHO | 7RPH | Commercial 7HT | Hobart | 1080 | AM | Moved to FM in 1998 as 7XXX | 7TAB (HPON) | Commercial 7LA | Launceston | 1098 | AM | Moved to FM in 2008 as 7LAA | silent | Commercial 7NT | Launceston | 0711 | AM | Moved to FM in 2006, retained call | silent | National 7QN | Queenstown | 0630 | AM | Moved to FM in 1991, retained call | 7RN | National 7QT | Queenstown | 0837 | AM | Changed call to 7XS in 1988 | 7XS | Commercial 7UV | Ulverstone | | AM | Moved to Devonport and changed call to 7AD in 1940 | 7AD | Commercial 7ZL | Hobart | 0603 | AM | Changed call to 7RN in 1991 | 7RN | National
WTQ_for_TSD
Callsign | Area served | Frequency | Band | Fate | Freq currently | Purpose 7CAE | Hobart | 092.1 | FM | Changed call to 7THE ca. 1980 | 7THE | Community 7DY | Derby | | AM | Moved to Scottsdale and changed call to 7SD in 1954 | 7SD | Commercial 7EX | Launceston | 1008 | AM | Moved to FM in 2008 as 7EXX | silent | Commercial 7HO | Hobart | 0864 | AM | Moved to FM in 1990 as 7HHO | 7RPH | Commercial 7HT | Hobart | 1080 | AM | Moved to FM in 1998 as 7XXX | 7TAB (HPON) | Commercial 7LA | Launceston | 1098 | AM | Moved to FM in 2008 as 7LAA | silent | Commercial 7NT | Launceston | 0711 | AM | Moved to FM in 2006, retained call | silent | National 7QN | Queenstown | 0630 | AM | Moved to FM in 1991, retained call | 7RN | National 7QT | Queenstown | 0837 | AM | Changed call to 7XS in 1988 | 7XS | Commercial 7UV | Ulverstone | | AM | Moved to Devonport and changed call to 7AD in 1940 | 7AD | Commercial 7ZL | Hobart | 0603 | AM | Changed call to 7RN in 1991 | 7RN | National
Please ascertain the quantity of rows and columns within the provided table. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_246
WTQ_204-csv_653.jpg
This image displays a table. Could you provide me with the row number and column number corresponding to this table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Chord | Root | Minor Third | Perfect Fifth | Major Seventh CmM7 | C | E♭ | G | B C♯mM7 | C♯ | E | G♯ | B♯ (C) D♭mM7 | D♭ | F♭ (E) | A♭ | C DmM7 | D | F | A | C♯ D♯mM7 | D♯ | F♯ | A♯ | C (D) E♭mM7 | E♭ | G♭ | B♭ | D EmM7 | E | G | B | D♯ FmM7 | F | A♭ | C | E F♯mM7 | F♯ | A | C♯ | E♯ (F) G♭mM7 | G♭ | B (A) | D♭ | F GmM7 | G | B♭ | D | F♯ G♯mM7 | G♯ | B | D♯ | F (G) A♭mM7 | A♭ | C♭ (B) | E♭ | G AmM7 | A | C | E | G♯ A♯mM7 | A♯ | C♯ | E♯ (F) | G (A) B♭mM7 | B♭ | D♭ | F | A BmM7 | B | D | F♯ | A♯
WTQ_for_TSD
Chord | Root | Minor Third | Perfect Fifth | Major Seventh CmM7 | C | E♭ | G | B C♯mM7 | C♯ | E | G♯ | B♯ (C) D♭mM7 | D♭ | F♭ (E) | A♭ | C DmM7 | D | F | A | C♯ D♯mM7 | D♯ | F♯ | A♯ | C (D) E♭mM7 | E♭ | G♭ | B♭ | D EmM7 | E | G | B | D♯ FmM7 | F | A♭ | C | E F♯mM7 | F♯ | A | C♯ | E♯ (F) G♭mM7 | G♭ | B (A) | D♭ | F GmM7 | G | B♭ | D | F♯ G♯mM7 | G♯ | B | D♯ | F (G) A♭mM7 | A♭ | C♭ (B) | E♭ | G AmM7 | A | C | E | G♯ A♯mM7 | A♯ | C♯ | E♯ (F) | G (A) B♭mM7 | B♭ | D♭ | F | A BmM7 | B | D | F♯ | A♯
This image displays a table. Could you provide me with the row number and column number corresponding to this table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_247
WTQ_204-csv_827.jpg
I'd like to know the total number of rows and columns in the provided table. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Contestant | Original Tribe | Switched Tribe | Merged Tribe | Finish | Total Votes Yelena Kondulaynen 44.the actress | Pelicans | | | 1st Voted Out Day 3 | 5 Kris Kelmi 47.the singer | Barracudas | | | 2nd Voted Out Day 6 | 1 Aleksandr Pashutin 60.the actor | Barracudas | | | 3rd Voted Out Day 9 | 7 Igor' Livanov 49.the actor | Pelicans | | | Eliminated Day 11 | 0 Dana Borisova 26.the TV presenter | Pelicans | Barracudas | | 4th Voted Out Day 12 | 5 Aleksandr Byalko 50.the physicist | Pelicans | Barracudas | | 5th Voted Out Day 15 | 6 Tatyana Dogileva 45.the actress | Pelicans | Barracudas | | 6th Voted Out Day 18 | 3 Tat'yana Ovsiyenko 36.the singer | Barracudas | Pelicans | | Eliminated Day 19 | 1 Viktor Gusev 47.the sport commentator | Pelicans | Pelicans | Crocodiles | 7th Voted Out 1st Jury Member Day 21 | 6 Ivan Demidov 39.the TV presenter | Barracudas | Pelicans | Crocodiles | Eliminated 2nd Jury Member Day 23 | 3 Yelena Proklova 49.the TV presenter | Pelicans | Barracudas | Crocodiles | 8th Voted Out 3rd Jury Member Day 24 | 4 Marina Aleksandrova 20.the actress | Barracudas | Pelicans | Crocodiles | 9th Voted Out 4th Jury Member Day 27 | 6 Ivar Kalnynsh 54.the actor | | | Crocodiles | 10th Voted Out 5th Jury Member Day 30 | 3 Vera Glagoleva 46.the actress | | | Crocodiles | 11th Voted Out 6th Jury Member Day 33 | 4 Larisa Verbitskaya 43.the TV presenter | Barracudas | Pelicans | Crocodiles | 12th Voted Out 7th Jury Member Day 36 | 11 Aleksandr Lykov 41.the actor | Barracudas | Barracudas | Crocodiles | 13th Voted Out 8th Jury Member Day 37 | 6 Olga Orlova 25.the singer | Barracudas | Baracudas | Crocodiles | Eliminated 9th Jury Member Day 38 | 10 Yelena Perova 26.the singer | Pelicans | Pelicans | Crocodiles | Runner-Up | 2 Vladimir Presnyakov, Jr. 34.the singer | Pelicans | Pelicans | Crocodiles | Sole Survivor | 6
WTQ_for_TSD
Contestant | Original Tribe | Switched Tribe | Merged Tribe | Finish | Total Votes Yelena Kondulaynen 44.the actress | Pelicans | | | 1st Voted Out Day 3 | 5 Kris Kelmi 47.the singer | Barracudas | | | 2nd Voted Out Day 6 | 1 Aleksandr Pashutin 60.the actor | Barracudas | | | 3rd Voted Out Day 9 | 7 Igor' Livanov 49.the actor | Pelicans | | | Eliminated Day 11 | 0 Dana Borisova 26.the TV presenter | Pelicans | Barracudas | | 4th Voted Out Day 12 | 5 Aleksandr Byalko 50.the physicist | Pelicans | Barracudas | | 5th Voted Out Day 15 | 6 Tatyana Dogileva 45.the actress | Pelicans | Barracudas | | 6th Voted Out Day 18 | 3 Tat'yana Ovsiyenko 36.the singer | Barracudas | Pelicans | | Eliminated Day 19 | 1 Viktor Gusev 47.the sport commentator | Pelicans | Pelicans | Crocodiles | 7th Voted Out 1st Jury Member Day 21 | 6 Ivan Demidov 39.the TV presenter | Barracudas | Pelicans | Crocodiles | Eliminated 2nd Jury Member Day 23 | 3 Yelena Proklova 49.the TV presenter | Pelicans | Barracudas | Crocodiles | 8th Voted Out 3rd Jury Member Day 24 | 4 Marina Aleksandrova 20.the actress | Barracudas | Pelicans | Crocodiles | 9th Voted Out 4th Jury Member Day 27 | 6 Ivar Kalnynsh 54.the actor | | | Crocodiles | 10th Voted Out 5th Jury Member Day 30 | 3 Vera Glagoleva 46.the actress | | | Crocodiles | 11th Voted Out 6th Jury Member Day 33 | 4 Larisa Verbitskaya 43.the TV presenter | Barracudas | Pelicans | Crocodiles | 12th Voted Out 7th Jury Member Day 36 | 11 Aleksandr Lykov 41.the actor | Barracudas | Barracudas | Crocodiles | 13th Voted Out 8th Jury Member Day 37 | 6 Olga Orlova 25.the singer | Barracudas | Baracudas | Crocodiles | Eliminated 9th Jury Member Day 38 | 10 Yelena Perova 26.the singer | Pelicans | Pelicans | Crocodiles | Runner-Up | 2 Vladimir Presnyakov, Jr. 34.the singer | Pelicans | Pelicans | Crocodiles | Sole Survivor | 6
I'd like to know the total number of rows and columns in the provided table. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_248
WTQ_204-csv_304.jpg
Could you calculate the row number and column number in this table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Rank | Name | Nationality | Time | Notes | Points 1 | Adam Kszczot | Poland | 1:46.50 | | 12 2 | Jeff Lastennet | France | 1:46.70 | | 11 3 | Gareth Warburton | Great Britain | 1:46.95 | SB | 10 4 | Mario Scapini | Italy | 1:47.20 | PB | 9 5 | Anis Ananenka | Belarus | 1:47.29 | | 8 6 | Oleh Kayafa | Ukraine | 1:47.42 | | 7 7 | Joni Jaako | Sweden | 1:47.61 | SB | 6 8 | Robin Schembera | Germany | 1:47.79 | | 5 9 | Ivan Tukhtachev | Russia | 1:48.27 | SB | 4 10 | Antonio Manuel Reina | Spain | 1:48.56 | | 3 11 | António Rodrigues | Portugal | 1:50.45 | | 2 12 | Milan Kocourek | Czech Republic | 1:59.28 | | 1
WTQ_for_TSD
Rank | Name | Nationality | Time | Notes | Points 1 | Adam Kszczot | Poland | 1:46.50 | | 12 2 | Jeff Lastennet | France | 1:46.70 | | 11 3 | Gareth Warburton | Great Britain | 1:46.95 | SB | 10 4 | Mario Scapini | Italy | 1:47.20 | PB | 9 5 | Anis Ananenka | Belarus | 1:47.29 | | 8 6 | Oleh Kayafa | Ukraine | 1:47.42 | | 7 7 | Joni Jaako | Sweden | 1:47.61 | SB | 6 8 | Robin Schembera | Germany | 1:47.79 | | 5 9 | Ivan Tukhtachev | Russia | 1:48.27 | SB | 4 10 | Antonio Manuel Reina | Spain | 1:48.56 | | 3 11 | António Rodrigues | Portugal | 1:50.45 | | 2 12 | Milan Kocourek | Czech Republic | 1:59.28 | | 1
Could you calculate the row number and column number in this table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_249
WTQ_204-csv_803.jpg
Regarding the table displayed, can you identify how many rows and columns it has? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> Series # | Season # | Title | Notes | Original air date 1 | 1 | \The Charity\"" | Alfie, Dee Dee, and Melanie are supposed to be helping their parents at a carnival by working the dunking booth. When Goo arrives and announces their favorite basketball player, Kendall Gill, is at the Comic Book Store signing autographs, the boys decide to ditch the carnival. This leaves Melanie and Jennifer to work the booth and both end up soaked. But the Comic Book Store is packed and much to Alfie and Dee Dee's surprise their father has to interview Kendall Gill. Goo comes up with a plan to get Alfie and Dee Dee, Gill's signature before getting them back at the local carnival, but are caught by Roger. All ends well for everyone except Alfie and Goo, who must endure being soaked at the dunking booth. | October 15, 1994 2 | 1 | \The Practical Joke War\"" | Alfie and Goo unleash harsh practical jokes on Dee Dee and his friends. Dee Dee, Harry and Donnel retaliate by pulling a practical joke on Alfie with the trick gum. After Alfie and Goo get even with Dee Dee and his friends, Melanie and Deonne help them get even. Soon, Alfie and Goo declare a practical joke war on Melanie, Dee Dee and their friends. This eventually stops when Roger and Jennifer end up on the wrong end of the practical joke war after being announced as the winner of a magazine contest for Best Family Of The Year. They set their children straight for their behavior and will have a talk with their friends' parents as well. | October 22, 1994 3 | 1 | \The Weekend Aunt Helen Came\"" | The boy's mother, Jennifer, leaves for the weekend and she leaves the father, Roger, in charge. However, he lets the kids run wild. Alfie and Dee Dee's Aunt Helen then comes to oversee the house until Jennifer gets back. Meanwhile, Alfie throws a basketball at Goo, which hits him in the head, giving him temporary amnesia. In this case of memory loss, Goo acts like a nerd, does homework on a weekend, wants to be called Milton instead of Goo, and he even calls Alfie Alfred. He is much nicer to Deonne and Dee Dee, but is somewhat rude to Melanie. The only thing that will reverse this is another hit in the head. | November 1, 1994 4 | 1 | \Robin Hood Play\"" | Alfie's school is performing the play Robin Hood and Alfie is chosen to play the part of Robin Hood. Alfie is excited at this prospect, but he does not want to wear tights because he feels that tights are for girls. However, he reconsiders his stance on tights when Dee Dee wisely tells him not to let that affect his performance as Robin Hood. | November 9, 1994 5 | 1 | \Basketball Tryouts\"" | Alfie tries out for the basketball team and doesn't make it even after showing off his basketball skills. However, Harry, Dee Dee and Donnell make the team. Alfie is depressed and doesn't want to attend the celebration party. However, Goo sets him straight by telling him it was his own fault for not being a team player and kept the ball to himself. | November 30, 1994 6 | 1 | \Where's the Snake?\"" | Dee Dee gets a snake, but he doesn't want his parents to know about it. However, things get complicated when he loses the snake in the house. Meanwhile, Melanie and Deonne are assigned by their teacher to take care of her beloved pet rabbit, Duchess for the weekend. This causes both Alfie and Dee Dee to be concerned for Duchess when they learn from Goo that snakes eat rabbits. | December 6, 1994 7 | 1 | \Dee Dee's Girlfriend\"" | A girl kisses Dee Dee in front of Harry and Donnell. They promise not to tell, but it slips and everyone laughs at Dee Dee. Dee Dee ends his friendship with Harry and Donnell and hangs out with Alfie and Goo. Soon, Alfie and Goo finally get the three to talk to each other. | December 15, 1994 8 | 1 | \Dee Dee's Haircut\"" | Dee Dee wants to get a hair cut by Cool Doctor Money and have his name shaved in his head. His parents will not let him do this, but Goo offers to do it for five dollars. However, when Goo messes up Dee Dee's hair and spells his name wrong, his parents find out the truth and Dee Dee is forced to have his hair shaved off. In addition to that, his friends tease him about his bald head, causing a fight between the boys along with Goo and Alfie. In a b-story, Alfie and Goo try to play a practical joke on Dee Dee involving a jalapeño lollipop. It backfires when Roger is the unwitting victim and it leads to him chasing the boys around. | December 20, 1994 9 | 1 | \Dee Dee Runs Away\"" | Dee Dee has been waiting to go to a monster truck show all week. But Alfie and Goo's baseball team makes it to the tournament and everyone forgets about the monster truck show. Dee Dee feels ignored and runs away from home with Harry and Donnell. It's up to Alfie and Goo to try and convince him to come home. | December 28, 1994 10 | 1 | '\Donnell's Birthday Party\"" | Donnell is having a birthday party and brags about all the dancing and cool people who will be there. Harry says that he knows how to dance so Dee Dee feels left out because he doesn't know how to dance. Later on, Harry admits to Dee Dee alone that he can't dance either and only lied so he doesn't get teased by Donnell. So, they ask Alfie to help them learn how to dance. He refuses to help because Dee Dee previously told on him to Roger about his and Goo's plans to cheat on their math quiz. Alfie eventually agrees, after Melanie threatens to refuse to help him with his math homework. Soon Dee Dee and Harry learn Donnell's secret and were forced to teach him how to dance. After the party, Dee Dee tells Alfie about it and finds out that he knew Donnell was a liar. | January 5, 1995 11 | 1 | \Alfie's Birthday Party\"" | Goo and Melanie pretend they are dating and they leave Alfie out of everything. He ends up bored and starts hanging out with Dee Dee and his friends. However, it just isn't the same without Goo. Later on, Alfie learns about the surprise birthday party that Goo and Melanie had been planning with everyone else (except for Dee Dee, who couldn't know since he would've told). | January 19, 1995 12 | 1 | \Candy Sale\"" | Alfie and Goo are selling candy to make money for some expensive jackets, but they are not having any luck. However, when Dee Dee start helping them sell candy, they start to make money and asks him to help them out. Soon Goo and Alfie finds themselves confronted by Melanie, Deonne, Harry and Donnell for Dee Dee's share of the money. They soon learn the boys have used the money to buy three expensive jackets for themselves and Dee Dee as a token of their gratitude. They quickly apologize to Alfie and Goo for their quick judgment. | January 26, 1995 13 | 1 | \The Big Bully\"" | Dee Dee gets beat up at school and his friends try to teach him how to fight back. Goo, however, tells him to bluff, but the plan backfires and Dee Dee gets hit because of it. When Alfie confronts the bully, he learns that Dee Dee was picked on by a girl. Alfie and Goo decide to confront her. However, when some of their classmates, who happen to be the girls' siblings, learn they are bullying their sister, they intervene. | February 2, 1995
WTQ_for_TSD
Series # | Season # | Title | Notes | Original air date 1 | 1 | \The Charity\"" | Alfie, Dee Dee, and Melanie are supposed to be helping their parents at a carnival by working the dunking booth. When Goo arrives and announces their favorite basketball player, Kendall Gill, is at the Comic Book Store signing autographs, the boys decide to ditch the carnival. This leaves Melanie and Jennifer to work the booth and both end up soaked. But the Comic Book Store is packed and much to Alfie and Dee Dee's surprise their father has to interview Kendall Gill. Goo comes up with a plan to get Alfie and Dee Dee, Gill's signature before getting them back at the local carnival, but are caught by Roger. All ends well for everyone except Alfie and Goo, who must endure being soaked at the dunking booth. | October 15, 1994 2 | 1 | \The Practical Joke War\"" | Alfie and Goo unleash harsh practical jokes on Dee Dee and his friends. Dee Dee, Harry and Donnel retaliate by pulling a practical joke on Alfie with the trick gum. After Alfie and Goo get even with Dee Dee and his friends, Melanie and Deonne help them get even. Soon, Alfie and Goo declare a practical joke war on Melanie, Dee Dee and their friends. This eventually stops when Roger and Jennifer end up on the wrong end of the practical joke war after being announced as the winner of a magazine contest for Best Family Of The Year. They set their children straight for their behavior and will have a talk with their friends' parents as well. | October 22, 1994 3 | 1 | \The Weekend Aunt Helen Came\"" | The boy's mother, Jennifer, leaves for the weekend and she leaves the father, Roger, in charge. However, he lets the kids run wild. Alfie and Dee Dee's Aunt Helen then comes to oversee the house until Jennifer gets back. Meanwhile, Alfie throws a basketball at Goo, which hits him in the head, giving him temporary amnesia. In this case of memory loss, Goo acts like a nerd, does homework on a weekend, wants to be called Milton instead of Goo, and he even calls Alfie Alfred. He is much nicer to Deonne and Dee Dee, but is somewhat rude to Melanie. The only thing that will reverse this is another hit in the head. | November 1, 1994 4 | 1 | \Robin Hood Play\"" | Alfie's school is performing the play Robin Hood and Alfie is chosen to play the part of Robin Hood. Alfie is excited at this prospect, but he does not want to wear tights because he feels that tights are for girls. However, he reconsiders his stance on tights when Dee Dee wisely tells him not to let that affect his performance as Robin Hood. | November 9, 1994 5 | 1 | \Basketball Tryouts\"" | Alfie tries out for the basketball team and doesn't make it even after showing off his basketball skills. However, Harry, Dee Dee and Donnell make the team. Alfie is depressed and doesn't want to attend the celebration party. However, Goo sets him straight by telling him it was his own fault for not being a team player and kept the ball to himself. | November 30, 1994 6 | 1 | \Where's the Snake?\"" | Dee Dee gets a snake, but he doesn't want his parents to know about it. However, things get complicated when he loses the snake in the house. Meanwhile, Melanie and Deonne are assigned by their teacher to take care of her beloved pet rabbit, Duchess for the weekend. This causes both Alfie and Dee Dee to be concerned for Duchess when they learn from Goo that snakes eat rabbits. | December 6, 1994 7 | 1 | \Dee Dee's Girlfriend\"" | A girl kisses Dee Dee in front of Harry and Donnell. They promise not to tell, but it slips and everyone laughs at Dee Dee. Dee Dee ends his friendship with Harry and Donnell and hangs out with Alfie and Goo. Soon, Alfie and Goo finally get the three to talk to each other. | December 15, 1994 8 | 1 | \Dee Dee's Haircut\"" | Dee Dee wants to get a hair cut by Cool Doctor Money and have his name shaved in his head. His parents will not let him do this, but Goo offers to do it for five dollars. However, when Goo messes up Dee Dee's hair and spells his name wrong, his parents find out the truth and Dee Dee is forced to have his hair shaved off. In addition to that, his friends tease him about his bald head, causing a fight between the boys along with Goo and Alfie. In a b-story, Alfie and Goo try to play a practical joke on Dee Dee involving a jalapeño lollipop. It backfires when Roger is the unwitting victim and it leads to him chasing the boys around. | December 20, 1994 9 | 1 | \Dee Dee Runs Away\"" | Dee Dee has been waiting to go to a monster truck show all week. But Alfie and Goo's baseball team makes it to the tournament and everyone forgets about the monster truck show. Dee Dee feels ignored and runs away from home with Harry and Donnell. It's up to Alfie and Goo to try and convince him to come home. | December 28, 1994 10 | 1 | '\Donnell's Birthday Party\"" | Donnell is having a birthday party and brags about all the dancing and cool people who will be there. Harry says that he knows how to dance so Dee Dee feels left out because he doesn't know how to dance. Later on, Harry admits to Dee Dee alone that he can't dance either and only lied so he doesn't get teased by Donnell. So, they ask Alfie to help them learn how to dance. He refuses to help because Dee Dee previously told on him to Roger about his and Goo's plans to cheat on their math quiz. Alfie eventually agrees, after Melanie threatens to refuse to help him with his math homework. Soon Dee Dee and Harry learn Donnell's secret and were forced to teach him how to dance. After the party, Dee Dee tells Alfie about it and finds out that he knew Donnell was a liar. | January 5, 1995 11 | 1 | \Alfie's Birthday Party\"" | Goo and Melanie pretend they are dating and they leave Alfie out of everything. He ends up bored and starts hanging out with Dee Dee and his friends. However, it just isn't the same without Goo. Later on, Alfie learns about the surprise birthday party that Goo and Melanie had been planning with everyone else (except for Dee Dee, who couldn't know since he would've told). | January 19, 1995 12 | 1 | \Candy Sale\"" | Alfie and Goo are selling candy to make money for some expensive jackets, but they are not having any luck. However, when Dee Dee start helping them sell candy, they start to make money and asks him to help them out. Soon Goo and Alfie finds themselves confronted by Melanie, Deonne, Harry and Donnell for Dee Dee's share of the money. They soon learn the boys have used the money to buy three expensive jackets for themselves and Dee Dee as a token of their gratitude. They quickly apologize to Alfie and Goo for their quick judgment. | January 26, 1995 13 | 1 | \The Big Bully\"" | Dee Dee gets beat up at school and his friends try to teach him how to fight back. Goo, however, tells him to bluff, but the plan backfires and Dee Dee gets hit because of it. When Alfie confronts the bully, he learns that Dee Dee was picked on by a girl. Alfie and Goo decide to confront her. However, when some of their classmates, who happen to be the girls' siblings, learn they are bullying their sister, they intervene. | February 2, 1995
Regarding the table displayed, can you identify how many rows and columns it has? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_250
WTQ_204-csv_167.jpg
How many rows and columns does this table have? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> No. | Score | Player | Team | Balls | Inns. | Opposing team | Date | Result 1 | 123 | Kris Srikkanth | India | 103 | 1 | Pakistan | 18 February 1987 | Lost 2 | 107* | Desmond Haynes | West Indies | 137 | 1 | Pakistan | 1 November 1989 | Lost 3 | 100* | Sachin Tendulkar | India | 103 | 2 | Kenya | 31 May 1998 | Won 4 | 121 | Marcus Trescothick | England | 109 | 2 | India | 19 January 2002 | Lost 5 | 108* | Salman Butt | Pakistan | 130 | 2 | India | 13 November 2004 | Won 6 | 134* | Graeme Smith | South Africa | 124 | 2 | India | 25 November 2005 | Won 7 | 118 | Upul Tharanga | Sri Lanka | 128 | 1 | India | 24 December 2009 | Lost 8 | 150* | Gautam Gambhir | India | 137 | 2 | Sri Lanka | 24 December 2009 | Won 9 | 107 | Virat Kohli | India | 114 | 2 | Sri Lanka | 24 December 2009 | Won 10 | 106 | Ryan ten Doeschate | Netherlands | 108 | 1 | Ireland | 18 March 2011 | Lost 11 | 101 | Paul Stirling | Ireland | 72 | 2 | Netherlands | 18 March 2011 | Won 12 | 106 | Nasir Jamshed | Pakistan | 124 | 1 | India | 3 January 2013 | Won
WTQ_for_TSD
No. | Score | Player | Team | Balls | Inns. | Opposing team | Date | Result 1 | 123 | Kris Srikkanth | India | 103 | 1 | Pakistan | 18 February 1987 | Lost 2 | 107* | Desmond Haynes | West Indies | 137 | 1 | Pakistan | 1 November 1989 | Lost 3 | 100* | Sachin Tendulkar | India | 103 | 2 | Kenya | 31 May 1998 | Won 4 | 121 | Marcus Trescothick | England | 109 | 2 | India | 19 January 2002 | Lost 5 | 108* | Salman Butt | Pakistan | 130 | 2 | India | 13 November 2004 | Won 6 | 134* | Graeme Smith | South Africa | 124 | 2 | India | 25 November 2005 | Won 7 | 118 | Upul Tharanga | Sri Lanka | 128 | 1 | India | 24 December 2009 | Lost 8 | 150* | Gautam Gambhir | India | 137 | 2 | Sri Lanka | 24 December 2009 | Won 9 | 107 | Virat Kohli | India | 114 | 2 | Sri Lanka | 24 December 2009 | Won 10 | 106 | Ryan ten Doeschate | Netherlands | 108 | 1 | Ireland | 18 March 2011 | Lost 11 | 101 | Paul Stirling | Ireland | 72 | 2 | Netherlands | 18 March 2011 | Won 12 | 106 | Nasir Jamshed | Pakistan | 124 | 1 | India | 3 January 2013 | Won
How many rows and columns does this table have? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_251
WTQ_204-csv_274.jpg
Please identify the row and column numbers of the table displayed in this image. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Speed | Date | Country | Train | Arr. | Power | State | Comments 202.6 km/h (126 mph) | 1938-07-03 | UK | LNER Class A4 No. 4468 Mallard | Loc | Steam | Unkn. | Downhill grade. Data indicates peak speed 202.6 km/h (126 mph), mean speed (half-mile) 201.2 km/h (125 mph). Mallard suffered an overheated crankpin during the run, but was repaired and returned to traffic within 9 days. 200.4 km/h (125 mph) | 1936-05-11 | Germany | Borsig DRG series 05 002 | Loc | Steam | Unkn. | Level grade.[citation needed] 185.07 km/h (115 mph) | 1905-06-11 | USA | Pennsylvania Railroad E2 #7002 | Loc | Steam | Unmod. | Claimed.[by whom?] Clocked at Crestline, Ohio at 127.1 mph (205 km/h) in 1905. However PRR Steam Locomotives did not carry speedometers at that time, speed was calculated by measuring time between mile markers, so this is not recognized as a speed record.[citation needed] 182.4 km/h (113 mph) | 1972-10-11 | Germany | BR 18 201 | Loc | Steam | Unkn. | The fastest operational steam locomotive as of 2011.[citation needed] 181.1 km/h (113 mph) | 1935-04-05 | USA | Milwaukee Road class A #2 | Loc | Steam | Unkn. | Claimed[by whom?] to have sustained 112.5 mph (181 km/h) for 14 miles (23 km). Average speed for 136 miles (219 km) between Milwaukee and New Lisbon, Wisconsin was 74.9 mph (121 km/h). 180.3 km/h (112 mph) | 1935-09-29 | UK | LNER Class A4 2509 Silver Link | Loc | Steam | Unkn. | Authenticated. Some sources say 112.5 mph.[citation needed] 168.5 km/h (105 mph) | 1935-03-05 | UK | LNER Class A3 No. 2750 Papyrus | Loc | Steam | Unmod. | First run at 100+ mph with complete, surviving documentation.[citation needed] 166.6 km/h (104 mph) | 1934-07-20 | USA | Milwaukee Road class F6 #6402 | Loc | Steam | Unmod | A point between Oakwood, Illinois and Lake, Wisconsin. Also averaged 75.5 mph (122 km/h) on 85 miles (137 km) from Chicago, Illinois to Milwaukee, and 89.92 mph (145 km/h) for a 68.9 miles (110.9 km) stretch 164 km/h (102 mph) | 1904-05-09 | UK | GWR 3700 Class 3440 City of Truro | Loc | Steam | Unmod. | Claimed[by whom?] to be the first steam locomotive to reach100 mph (161 km/h).[citation needed] 161 km/h (100 mph) | 1934-11-30 | UK | LNER Class A3 4472 Flying Scotsman | Loc | Steam | Unmod. | In 1934, Flying Scotsman achieved the first authenticated 100 mph (161 km/h) by a steam locomotive. 145 km/h (90 mph) | 1895-08-22 | UK | LNWR No. 790 Hardwicke | Loc | Steam | Unmod. | Maximum speed claimed[by whom?], although average speed record was authenticated.[citation needed] 131.6 km/h (82 mph) | 1854-06 | UK | Bristol & Exeter Railway #41 | Loc | Steam | Unmod. | Broad gauge[citation needed] 131 km/h (81 mph) | 1893-05-10 | USA | Empire State Express No. 999 | Loc | Steam | Unmod. | 112 mph (180 km/h) claimed[by whom?], which would make it the first wheeled vehicle to exceed 100 mph (161 km/h). 125.6 km/h (78 mph) | 1850 | UK | Great Britain | Loc | Steam | Unmod. | 80 mph (129 km/h) claimed[by whom?][citation needed] 96.6 km/h (60 mph) | 1848 | USA | Boston and Maine Railroad Antelope | Loc | Steam | Unmod. | First authenticated 60 mph (97 km/h),26 miles (42 km) in 26 minutes.[citation needed] 48 km/h (30 mph) | 1830 | UK | Stephenson's Rocket | Loc | Steam | Unmod. | [citation needed] 24 km/h (15 mph) | 1825 | UK | Locomotion No. 1 | Loc | Steam | Unmod. | [citation needed] 8 km/h (5 mph) | 1804-02-21 | UK | Richard Trevithick's world's first railway steam locomotive | Loc | Steam | Unmod. | [citation needed]
WTQ_for_TSD
Speed | Date | Country | Train | Arr. | Power | State | Comments 202.6 km/h (126 mph) | 1938-07-03 | UK | LNER Class A4 No. 4468 Mallard | Loc | Steam | Unkn. | Downhill grade. Data indicates peak speed 202.6 km/h (126 mph), mean speed (half-mile) 201.2 km/h (125 mph). Mallard suffered an overheated crankpin during the run, but was repaired and returned to traffic within 9 days. 200.4 km/h (125 mph) | 1936-05-11 | Germany | Borsig DRG series 05 002 | Loc | Steam | Unkn. | Level grade.[citation needed] 185.07 km/h (115 mph) | 1905-06-11 | USA | Pennsylvania Railroad E2 #7002 | Loc | Steam | Unmod. | Claimed.[by whom?] Clocked at Crestline, Ohio at 127.1 mph (205 km/h) in 1905. However PRR Steam Locomotives did not carry speedometers at that time, speed was calculated by measuring time between mile markers, so this is not recognized as a speed record.[citation needed] 182.4 km/h (113 mph) | 1972-10-11 | Germany | BR 18 201 | Loc | Steam | Unkn. | The fastest operational steam locomotive as of 2011.[citation needed] 181.1 km/h (113 mph) | 1935-04-05 | USA | Milwaukee Road class A #2 | Loc | Steam | Unkn. | Claimed[by whom?] to have sustained 112.5 mph (181 km/h) for 14 miles (23 km). Average speed for 136 miles (219 km) between Milwaukee and New Lisbon, Wisconsin was 74.9 mph (121 km/h). 180.3 km/h (112 mph) | 1935-09-29 | UK | LNER Class A4 2509 Silver Link | Loc | Steam | Unkn. | Authenticated. Some sources say 112.5 mph.[citation needed] 168.5 km/h (105 mph) | 1935-03-05 | UK | LNER Class A3 No. 2750 Papyrus | Loc | Steam | Unmod. | First run at 100+ mph with complete, surviving documentation.[citation needed] 166.6 km/h (104 mph) | 1934-07-20 | USA | Milwaukee Road class F6 #6402 | Loc | Steam | Unmod | A point between Oakwood, Illinois and Lake, Wisconsin. Also averaged 75.5 mph (122 km/h) on 85 miles (137 km) from Chicago, Illinois to Milwaukee, and 89.92 mph (145 km/h) for a 68.9 miles (110.9 km) stretch 164 km/h (102 mph) | 1904-05-09 | UK | GWR 3700 Class 3440 City of Truro | Loc | Steam | Unmod. | Claimed[by whom?] to be the first steam locomotive to reach100 mph (161 km/h).[citation needed] 161 km/h (100 mph) | 1934-11-30 | UK | LNER Class A3 4472 Flying Scotsman | Loc | Steam | Unmod. | In 1934, Flying Scotsman achieved the first authenticated 100 mph (161 km/h) by a steam locomotive. 145 km/h (90 mph) | 1895-08-22 | UK | LNWR No. 790 Hardwicke | Loc | Steam | Unmod. | Maximum speed claimed[by whom?], although average speed record was authenticated.[citation needed] 131.6 km/h (82 mph) | 1854-06 | UK | Bristol & Exeter Railway #41 | Loc | Steam | Unmod. | Broad gauge[citation needed] 131 km/h (81 mph) | 1893-05-10 | USA | Empire State Express No. 999 | Loc | Steam | Unmod. | 112 mph (180 km/h) claimed[by whom?], which would make it the first wheeled vehicle to exceed 100 mph (161 km/h). 125.6 km/h (78 mph) | 1850 | UK | Great Britain | Loc | Steam | Unmod. | 80 mph (129 km/h) claimed[by whom?][citation needed] 96.6 km/h (60 mph) | 1848 | USA | Boston and Maine Railroad Antelope | Loc | Steam | Unmod. | First authenticated 60 mph (97 km/h),26 miles (42 km) in 26 minutes.[citation needed] 48 km/h (30 mph) | 1830 | UK | Stephenson's Rocket | Loc | Steam | Unmod. | [citation needed] 24 km/h (15 mph) | 1825 | UK | Locomotion No. 1 | Loc | Steam | Unmod. | [citation needed] 8 km/h (5 mph) | 1804-02-21 | UK | Richard Trevithick's world's first railway steam locomotive | Loc | Steam | Unmod. | [citation needed]
Please identify the row and column numbers of the table displayed in this image. Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_252
WTQ_203-csv_433.jpg
For the shown table, how many rows and columns are there? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Time | Wind | Auto | Athlete | Nationality | Location of race | Date 20.6y | | | Andy Stanfield | United States | Philadelphia, United States | May 26, 1951 20.6 | | | Andy Stanfield | United States | Los Angeles, United States | June 28, 1952 20.6 | 0.0 | | Thane Baker | United States | Bakersfield, United States | June 23, 1956 20.6 | | 20.75 | Bobby Morrow | United States | Melbourne, Australia | November 27, 1956 20.6 | | | Manfred Germar | West Germany | Wuppertal, Germany | October 1, 1958 20.6y | −1.6 | | Ray Norton | United States | Berkeley, United States | March 19, 1960 20.6 | | | Ray Norton | United States | Philadelphia, United States | April 30, 1960 20.5y | | | Peter Radford | United Kingdom | Wolverhampton, United Kingdom | May 28, 1960 20.5 | 0.0 | 20.75 | Stone Johnson | United States | Stanford, United States | July 2, 1960 20.5 | 0.0 | | Ray Norton | United States | Stanford, United States | July 2, 1960 20.5 | | 20.65 | Livio Berruti | Italy | Rome, Italy | September 3, 1960 20.5 | | 20.62 | Livio Berruti | Italy | Rome, Italy | September 3, 1960 20.5y | −1.1 | 20.67 | Paul Drayton | United States | Walnut, United States | June 23, 1962 20.3y | −0.1 | | Henry Carr | United States | Tempe, United States | March 23, 1963 20.2y | 0.5 | | Henry Carr | United States | Tempe, United States | April 4, 1964 20.0y | 0.0 | | Tommie Smith | United States | Sacramento, United States | June 11, 1968 19.8A | 0.9 | 19.83A | Tommie Smith | United States | Mexico City, Mexico | October 16, 1968 19.8A | 0.9 | 19.86A | Donald Quarrie | Jamaica | Cali, Colombia | August 3, 1971 19.8+ | 1.3 | | Donald Quarrie | Jamaica | Eugene, Oregon, United States | June 7, 1975
WTQ_for_TSD
Time | Wind | Auto | Athlete | Nationality | Location of race | Date 20.6y | | | Andy Stanfield | United States | Philadelphia, United States | May 26, 1951 20.6 | | | Andy Stanfield | United States | Los Angeles, United States | June 28, 1952 20.6 | 0.0 | | Thane Baker | United States | Bakersfield, United States | June 23, 1956 20.6 | | 20.75 | Bobby Morrow | United States | Melbourne, Australia | November 27, 1956 20.6 | | | Manfred Germar | West Germany | Wuppertal, Germany | October 1, 1958 20.6y | −1.6 | | Ray Norton | United States | Berkeley, United States | March 19, 1960 20.6 | | | Ray Norton | United States | Philadelphia, United States | April 30, 1960 20.5y | | | Peter Radford | United Kingdom | Wolverhampton, United Kingdom | May 28, 1960 20.5 | 0.0 | 20.75 | Stone Johnson | United States | Stanford, United States | July 2, 1960 20.5 | 0.0 | | Ray Norton | United States | Stanford, United States | July 2, 1960 20.5 | | 20.65 | Livio Berruti | Italy | Rome, Italy | September 3, 1960 20.5 | | 20.62 | Livio Berruti | Italy | Rome, Italy | September 3, 1960 20.5y | −1.1 | 20.67 | Paul Drayton | United States | Walnut, United States | June 23, 1962 20.3y | −0.1 | | Henry Carr | United States | Tempe, United States | March 23, 1963 20.2y | 0.5 | | Henry Carr | United States | Tempe, United States | April 4, 1964 20.0y | 0.0 | | Tommie Smith | United States | Sacramento, United States | June 11, 1968 19.8A | 0.9 | 19.83A | Tommie Smith | United States | Mexico City, Mexico | October 16, 1968 19.8A | 0.9 | 19.86A | Donald Quarrie | Jamaica | Cali, Colombia | August 3, 1971 19.8+ | 1.3 | | Donald Quarrie | Jamaica | Eugene, Oregon, United States | June 7, 1975
For the shown table, how many rows and columns are there? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_253
WTQ_203-csv_75.jpg
Could you count the number of rows and columns in this table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Date | Opponent | Score | Result | Record May 22 | Seattle | 75-64 | Win | 1-0 May 24 | @ Phoenix | 69-62 | Win | 2-0 May 30 | Connecticut | 83-91 | Loss | 2-1 June 1 | @ Minnesota | 64-68 (OT) | Loss | 2-2 June 3 | Phoenix | 66-51 | Win | 3-2 June 6 | @ Charlotte | 58-69 | Loss | 3-3 June 7 | @ Connecticut | 58-65 | Loss | 3-4 June 10 | Sacramento | 71-66 | Win | 4-4 June 14 | @ Phoenix | 61-76 | Loss | 4-5 June 17 | @ Minnesota | 77-68 | Win | 5-5 June 20 | @ San Antonio | 69-76 | Loss | 5-6 June 21 | Cleveland | 63-62 | Win | 6-6 June 24 | Los Angeles | 62-71 | Loss | 6-7 June 28 | San Antonio | 64-49 | Win | 7-7 July 1 | Minnesota | 71-69 | Win | 8-7 July 5 | Washington | 76-54 | Win | 9-7 July 8 | Indiana | 60-56 | Win | 10-7 July 15 | @ Seattle | 55-69 | Loss | 10-8 July 18 | @ Los Angeles | 79-74 | Win | 11-8 July 19 | @ Sacramento | 74-71 | Win | 12-8 July 26 | New York | 61-53 | Win | 13-8 July 29 | Minnesota | 73-58 | Win | 14-8 August 1 | @ San Antonio | 53-63 | Loss | 14-9 August 2 | San Antonio | 64-55 | Win | 15-9 August 5 | Sacramento | 74-47 | Win | 16-9 August 7 | @ Indiana | 68-55 | Win | 17-9 August 8 | @ Detroit | 66-56 | Win | 18-9 August 10 | Phoenix | 69-46 | Win | 19-9 August 16 | Los Angeles | 63-64 | Loss | 19-10 August 18 | @ New York | 64-67 | Loss | 19-11 August 19 | Seattle | 52-47 | Win | 20-11 August 21 | @ Sacramento | 52-64 | Loss | 20-12 August 23 | @ Seattle | 64-71 | Loss | 20-13 August 25 | @ Los Angeles | 64-67 | Loss | 20-14 August 29 (First Round, Game 1) | @ Sacramento | 59-65 | Loss | 0-1 August 31 (First Round, Game 2) | Sacramento | 69-48 | Win | 1-1 September 2 (First Round, Game 3) | Sacramento | 68-70 | Loss | 1-2
WTQ_for_TSD
Date | Opponent | Score | Result | Record May 22 | Seattle | 75-64 | Win | 1-0 May 24 | @ Phoenix | 69-62 | Win | 2-0 May 30 | Connecticut | 83-91 | Loss | 2-1 June 1 | @ Minnesota | 64-68 (OT) | Loss | 2-2 June 3 | Phoenix | 66-51 | Win | 3-2 June 6 | @ Charlotte | 58-69 | Loss | 3-3 June 7 | @ Connecticut | 58-65 | Loss | 3-4 June 10 | Sacramento | 71-66 | Win | 4-4 June 14 | @ Phoenix | 61-76 | Loss | 4-5 June 17 | @ Minnesota | 77-68 | Win | 5-5 June 20 | @ San Antonio | 69-76 | Loss | 5-6 June 21 | Cleveland | 63-62 | Win | 6-6 June 24 | Los Angeles | 62-71 | Loss | 6-7 June 28 | San Antonio | 64-49 | Win | 7-7 July 1 | Minnesota | 71-69 | Win | 8-7 July 5 | Washington | 76-54 | Win | 9-7 July 8 | Indiana | 60-56 | Win | 10-7 July 15 | @ Seattle | 55-69 | Loss | 10-8 July 18 | @ Los Angeles | 79-74 | Win | 11-8 July 19 | @ Sacramento | 74-71 | Win | 12-8 July 26 | New York | 61-53 | Win | 13-8 July 29 | Minnesota | 73-58 | Win | 14-8 August 1 | @ San Antonio | 53-63 | Loss | 14-9 August 2 | San Antonio | 64-55 | Win | 15-9 August 5 | Sacramento | 74-47 | Win | 16-9 August 7 | @ Indiana | 68-55 | Win | 17-9 August 8 | @ Detroit | 66-56 | Win | 18-9 August 10 | Phoenix | 69-46 | Win | 19-9 August 16 | Los Angeles | 63-64 | Loss | 19-10 August 18 | @ New York | 64-67 | Loss | 19-11 August 19 | Seattle | 52-47 | Win | 20-11 August 21 | @ Sacramento | 52-64 | Loss | 20-12 August 23 | @ Seattle | 64-71 | Loss | 20-13 August 25 | @ Los Angeles | 64-67 | Loss | 20-14 August 29 (First Round, Game 1) | @ Sacramento | 59-65 | Loss | 0-1 August 31 (First Round, Game 2) | Sacramento | 69-48 | Win | 1-1 September 2 (First Round, Game 3) | Sacramento | 68-70 | Loss | 1-2
Could you count the number of rows and columns in this table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_254
WTQ_203-csv_472.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> Season/Torneo | Jornada or Other | Home Team | Result | Away Team | Stadium | Date 1983–1984 season | 2 | Chivas | 1–1 | América | Estadio Jalisco | 11 September 1983 1983–1984 season | 21 | América | 1–1 | Chivas | Estadio Azteca | 22 January 1984 1983–1984 season | Final Ida | Chivas | 2–2 | América | Estadio Jalisco | 7 June 1984 1983–1984 season | Final Vuelta | América | 3–1 | Chivas | Estadio Azteca | 10 June 1984 1984–1985 season | 13 | América | 0–0 | Chivas | Estadio Azteca | 11 December 1984 1984–1985 season | 32 | Chivas | 0–0 | América | Estadio Jalisco | 24 March 1985 1984–1985 season | Quarterfinals Ida | Chivas | 0–2 | América | Estadio Jalisco | 7 May 1985 1984–1985 season | Quarterfinals Vuelta | América | 1–0 | Chivas | Estadio Azteca | 12 May 1985 1986–1987 season | 3 | América | 1–0 | Chivas | Estadio Azteca | 17 August 1986 1986–1987 season | 24 | Chivas | 2–2 | América | Estadio Jalisco | 11 January 1987 1987–1988 Season | 15 | América | 1–0 | Chivas | Estadio Azteca | 20 December 1987 1987–1988 season | 34 | Chivas | 3–2 | América | Estadio Jalisco | 15 May 1988 1988–1989 season | 12 | Chivas | 2–2 | América | Estadio Jalisco | 29 December 1988 1988–1989 season | 31 | América | 3–1 | Chivas | Estadio Azteca | 30 April 1989 1988-1989 Season | Liguilla | América | 2-1 | Chivas | Estadio Azteca | June 22, 1989 1988-1989 Season | Liquilla | Chivas | 1-2 | América | Estadio Jalisco | June 25, 1989 1989-1990 Season | 3 | Chivas | 2-2 | América | Estadio Jalisco | September 24, 1989 1989-1990 Season | 22 | América | 2-2 | Chivas | Estadio Azteca | January 14, 1990 1990-1991 Season | 12 | Chivas | 1-1 | América | Estadio Jalisco | December 9, 1990 1990-1991 Season | 31 | América | 2-2 | Chivas | Estadio Azteca | April 14, 1991 1990-1991 Season | Semifinals Ida | Chivas | 0-2 | América | Estadio Jalisco | June 13, 1991 1990-1991 Season | Semifinals Vuelta | América | 3-0 | Chivas | Estadio Azteca | June 16, 1991 1991-1992 Season | 2 | América | 1-1 | Chivas | Estadio Azteca | September 22, 1991 1991-1992 Season | 21 | Chivas | 0-0 | América | Estadio Jalisco | January 19, 1992 1992-1993 Season | 3 | Chivas | 1-0 | América | Estadio Jalisco | August 30, 1992 1992-1993 Season | 22 | América | 2-1 | Chivas | Estadio Azteca | January 10, 1993 1993-1994 Season | 4 | Chivas | 0-0 | América | Estadio Jalisco | September 5, 1993 1993-1994 Season | 23 | América | 1-0 | Chivas | Estadio Azteca | January 5, 1994 1994-1995 Season | 11 | Chivas | 3-4 | América | Estadio Jalisco | November 13, 1994 1994-1995 Season | 30 | América | 0-0 | Chivas | Estadio Azteca | March 19, 1995 1995-1996 Season | 9 | Chivas | 0-2 | América | Estadio Jalisco | October 22, 1995 1995-1996 Season | 26 | América | 2-3 | Chivas | Estadio Azteca | February 18, 1996 Invierno 1996 | 3 | Chivas | 5-0 | América | Estadio Jalisco | August 25, 1996 Verano 1997 | 3 | América | 0-0 | Chivas | Estadio Azteca | January 27, 1997 Invierno 1997 | 4 | Chivas | 1-2 | América | Estadio Jalisco | August 10, 1997 Invierno 1997 | Quarterfinals Ida | Chivas | 1-3 | América | Estadio Jalisco | November 18, 1997 Invierno 1997 | Quarterfinals Vuelta | América | 1-0 | Chivas | Estadio Azteca | November 21, 1997 Verano 1998 | 4 | América | 0-0 | Chivas | Estadio Azteca | January 15, 1998 Invierno 1998 | 8 | Chivas | 1-0 | América | Estadio Jalisco | September 20, 1998 Verano 1999 | 8 | América | 0-1 | Chivas | Estadio Azteca | March 7, 1999 Invierno 1999 | 5 | América | 2-0 | Chivas | Estadio Azteca | September 12, 1999 Invierno 1999 | Quarterfinals Ida | Chivas | 0-0 | América | Estadio Jalisco | December 2, 1999 Invierno 1999 | Quarterfinals Vuelta | América | 1-0 | Chivas | Estadio Azteca | December 5, 1999 Verano 2000 | 5 | Chivas | 3-0 | América | Estadio Jalisco | February 13, 2000 Invierno 2000 | 7 | América | 0-3 | Chivas | Estadio Azteca | September 10, 2000 Verano 2001 | 7 | Chivas | 1-2 | América | Estadio Jalisco | February 14, 2001 Invierno 2001 | 14 | Chivas | 1-1 | América | Estadio Jalisco | October 21, 2001 Verano 2002 | 14 | América | 2-3 | Chivas | Estadio Azteca | March 31, 2002 Apertura 2002 | 2 | Chivas | 0-1 | América | Estadio Jalisco | August 11, 2002 Clausura 2003 | 2 | América | 1-1 | Chivas | Estadio Azteca | January 19, 2002 Apertura 2003 | 17 | América | 1-2 | Chivas | Estadio Azteca | November 9, 2003 Clausura 2004 | 17 | Chivas | 0-1 | América | Estadio Jalisco | May 1, 2004 Apertura 2004 | 9 | Chivas | 1-1 | América | Estadio Jalisco | October 2, 2004 Clausura 2005 | 9 | América | 3-3 | Chivas | Estadio Azteca | March 13, 2005 Apertura 2005 | 7 | América | 0-0 | Chivas | Estadio Azteca | September 11, 2005 Clausura 2006 | 7 | Chivas | 1-0 | América | Estadio Jalisco | February 26, 2006 Apertura 2006 | 11 | Chivas | 2-0 | América | Estadio Jalisco | September 30, 2006 Apertura 2006 | Semifinals Ida | Chivas | 2-0 | América | Estadio Jalisco | November 30, 2006 Apertura 2006 | Semifinals Vuelta | América | 0-0 | Chivas | Estadio Azteca | December 3, 2006 Clausura 2007 | 11 | América | 1-0 | Chivas | Estadio Azteca | March 18, 2007 Clausura 2007 | Semifinals Ida | América | 1-0 | Chivas | Estadio Azteca | May 17, 2007 Clausura 2007 | Semifinals Vuelta | Chivas | 0-1 | América | Estadio Jalisco | May 20, 2007 Apertura 2007 | 14 | América | 2-1 | Chivas | Estadio Azteca | October 28, 2007 Clausura 2008 | 14 (Clasico 200) | Chivas | 3-2 | América | Estadio Jalisco | April 13, 2008 Apertura 2008 | 14 | América | 1-2 | Chivas | Estadio Azteca | October 26, 2008 Clausura 2009 | 14 | Chivas | 1-0 | América | Estadio Jalisco | April 19, 2009 Apertura 2009 | 13 | America | 1-0 | Chivas | Estadio Azteca | October 25, 2009 Bicentenario 2010 | 13 | Chivas | 1-0 | America | Estadio Jalisco | April 4, 2010 Apertura 2010 | 13 | América | 0-0 | Chivas | Estadio Azteca | October 24, 2010 Clausura 2011 | 13 | Chivas | 3-0 | America | Estadio Omnilife | April 10, 2011 Apertura 2011 | 14 | America | 1-3 | Chivas | Estadio Azteca | October 23, 2011 Clausura 2012 | 14 | Chivas | 0-1 | America | Estadio Omnilife | April 8, 2012 Apertura 2012 | 12 | America | 1-3 | Chivas | Estadio Azteca | October 6, 2012 Clausura 2013 | 12 | Chivas | 0-2 | America | Estadio Omnilife | March 31, 2013 Apertura 2013 | 13 | America | 2-0 | Chivas | Estadio Azteca | October 5, 2013 Clausura 2014 | 13 | Chivas | 0-4 | América | Estadio Omnilife | March 30, 2014
WTQ_for_TSD
Season/Torneo | Jornada or Other | Home Team | Result | Away Team | Stadium | Date 1983–1984 season | 2 | Chivas | 1–1 | América | Estadio Jalisco | 11 September 1983 1983–1984 season | 21 | América | 1–1 | Chivas | Estadio Azteca | 22 January 1984 1983–1984 season | Final Ida | Chivas | 2–2 | América | Estadio Jalisco | 7 June 1984 1983–1984 season | Final Vuelta | América | 3–1 | Chivas | Estadio Azteca | 10 June 1984 1984–1985 season | 13 | América | 0–0 | Chivas | Estadio Azteca | 11 December 1984 1984–1985 season | 32 | Chivas | 0–0 | América | Estadio Jalisco | 24 March 1985 1984–1985 season | Quarterfinals Ida | Chivas | 0–2 | América | Estadio Jalisco | 7 May 1985 1984–1985 season | Quarterfinals Vuelta | América | 1–0 | Chivas | Estadio Azteca | 12 May 1985 1986–1987 season | 3 | América | 1–0 | Chivas | Estadio Azteca | 17 August 1986 1986–1987 season | 24 | Chivas | 2–2 | América | Estadio Jalisco | 11 January 1987 1987–1988 Season | 15 | América | 1–0 | Chivas | Estadio Azteca | 20 December 1987 1987–1988 season | 34 | Chivas | 3–2 | América | Estadio Jalisco | 15 May 1988 1988–1989 season | 12 | Chivas | 2–2 | América | Estadio Jalisco | 29 December 1988 1988–1989 season | 31 | América | 3–1 | Chivas | Estadio Azteca | 30 April 1989 1988-1989 Season | Liguilla | América | 2-1 | Chivas | Estadio Azteca | June 22, 1989 1988-1989 Season | Liquilla | Chivas | 1-2 | América | Estadio Jalisco | June 25, 1989 1989-1990 Season | 3 | Chivas | 2-2 | América | Estadio Jalisco | September 24, 1989 1989-1990 Season | 22 | América | 2-2 | Chivas | Estadio Azteca | January 14, 1990 1990-1991 Season | 12 | Chivas | 1-1 | América | Estadio Jalisco | December 9, 1990 1990-1991 Season | 31 | América | 2-2 | Chivas | Estadio Azteca | April 14, 1991 1990-1991 Season | Semifinals Ida | Chivas | 0-2 | América | Estadio Jalisco | June 13, 1991 1990-1991 Season | Semifinals Vuelta | América | 3-0 | Chivas | Estadio Azteca | June 16, 1991 1991-1992 Season | 2 | América | 1-1 | Chivas | Estadio Azteca | September 22, 1991 1991-1992 Season | 21 | Chivas | 0-0 | América | Estadio Jalisco | January 19, 1992 1992-1993 Season | 3 | Chivas | 1-0 | América | Estadio Jalisco | August 30, 1992 1992-1993 Season | 22 | América | 2-1 | Chivas | Estadio Azteca | January 10, 1993 1993-1994 Season | 4 | Chivas | 0-0 | América | Estadio Jalisco | September 5, 1993 1993-1994 Season | 23 | América | 1-0 | Chivas | Estadio Azteca | January 5, 1994 1994-1995 Season | 11 | Chivas | 3-4 | América | Estadio Jalisco | November 13, 1994 1994-1995 Season | 30 | América | 0-0 | Chivas | Estadio Azteca | March 19, 1995 1995-1996 Season | 9 | Chivas | 0-2 | América | Estadio Jalisco | October 22, 1995 1995-1996 Season | 26 | América | 2-3 | Chivas | Estadio Azteca | February 18, 1996 Invierno 1996 | 3 | Chivas | 5-0 | América | Estadio Jalisco | August 25, 1996 Verano 1997 | 3 | América | 0-0 | Chivas | Estadio Azteca | January 27, 1997 Invierno 1997 | 4 | Chivas | 1-2 | América | Estadio Jalisco | August 10, 1997 Invierno 1997 | Quarterfinals Ida | Chivas | 1-3 | América | Estadio Jalisco | November 18, 1997 Invierno 1997 | Quarterfinals Vuelta | América | 1-0 | Chivas | Estadio Azteca | November 21, 1997 Verano 1998 | 4 | América | 0-0 | Chivas | Estadio Azteca | January 15, 1998 Invierno 1998 | 8 | Chivas | 1-0 | América | Estadio Jalisco | September 20, 1998 Verano 1999 | 8 | América | 0-1 | Chivas | Estadio Azteca | March 7, 1999 Invierno 1999 | 5 | América | 2-0 | Chivas | Estadio Azteca | September 12, 1999 Invierno 1999 | Quarterfinals Ida | Chivas | 0-0 | América | Estadio Jalisco | December 2, 1999 Invierno 1999 | Quarterfinals Vuelta | América | 1-0 | Chivas | Estadio Azteca | December 5, 1999 Verano 2000 | 5 | Chivas | 3-0 | América | Estadio Jalisco | February 13, 2000 Invierno 2000 | 7 | América | 0-3 | Chivas | Estadio Azteca | September 10, 2000 Verano 2001 | 7 | Chivas | 1-2 | América | Estadio Jalisco | February 14, 2001 Invierno 2001 | 14 | Chivas | 1-1 | América | Estadio Jalisco | October 21, 2001 Verano 2002 | 14 | América | 2-3 | Chivas | Estadio Azteca | March 31, 2002 Apertura 2002 | 2 | Chivas | 0-1 | América | Estadio Jalisco | August 11, 2002 Clausura 2003 | 2 | América | 1-1 | Chivas | Estadio Azteca | January 19, 2002 Apertura 2003 | 17 | América | 1-2 | Chivas | Estadio Azteca | November 9, 2003 Clausura 2004 | 17 | Chivas | 0-1 | América | Estadio Jalisco | May 1, 2004 Apertura 2004 | 9 | Chivas | 1-1 | América | Estadio Jalisco | October 2, 2004 Clausura 2005 | 9 | América | 3-3 | Chivas | Estadio Azteca | March 13, 2005 Apertura 2005 | 7 | América | 0-0 | Chivas | Estadio Azteca | September 11, 2005 Clausura 2006 | 7 | Chivas | 1-0 | América | Estadio Jalisco | February 26, 2006 Apertura 2006 | 11 | Chivas | 2-0 | América | Estadio Jalisco | September 30, 2006 Apertura 2006 | Semifinals Ida | Chivas | 2-0 | América | Estadio Jalisco | November 30, 2006 Apertura 2006 | Semifinals Vuelta | América | 0-0 | Chivas | Estadio Azteca | December 3, 2006 Clausura 2007 | 11 | América | 1-0 | Chivas | Estadio Azteca | March 18, 2007 Clausura 2007 | Semifinals Ida | América | 1-0 | Chivas | Estadio Azteca | May 17, 2007 Clausura 2007 | Semifinals Vuelta | Chivas | 0-1 | América | Estadio Jalisco | May 20, 2007 Apertura 2007 | 14 | América | 2-1 | Chivas | Estadio Azteca | October 28, 2007 Clausura 2008 | 14 (Clasico 200) | Chivas | 3-2 | América | Estadio Jalisco | April 13, 2008 Apertura 2008 | 14 | América | 1-2 | Chivas | Estadio Azteca | October 26, 2008 Clausura 2009 | 14 | Chivas | 1-0 | América | Estadio Jalisco | April 19, 2009 Apertura 2009 | 13 | America | 1-0 | Chivas | Estadio Azteca | October 25, 2009 Bicentenario 2010 | 13 | Chivas | 1-0 | America | Estadio Jalisco | April 4, 2010 Apertura 2010 | 13 | América | 0-0 | Chivas | Estadio Azteca | October 24, 2010 Clausura 2011 | 13 | Chivas | 3-0 | America | Estadio Omnilife | April 10, 2011 Apertura 2011 | 14 | America | 1-3 | Chivas | Estadio Azteca | October 23, 2011 Clausura 2012 | 14 | Chivas | 0-1 | America | Estadio Omnilife | April 8, 2012 Apertura 2012 | 12 | America | 1-3 | Chivas | Estadio Azteca | October 6, 2012 Clausura 2013 | 12 | Chivas | 0-2 | America | Estadio Omnilife | March 31, 2013 Apertura 2013 | 13 | America | 2-0 | Chivas | Estadio Azteca | October 5, 2013 Clausura 2014 | 13 | Chivas | 0-4 | América | Estadio Omnilife | March 30, 2014
This is a table picture. Can you figure out the row and column numbers for this particular table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_255
WTQ_203-csv_488.jpg
Please determine the total count of rows and columns in the provided table, respectively. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Year | Title | Genre | Publisher | Notes 1903 | Betty Zane | Historical | Charles Francis Press | 1906 | Spirit of the Border | Historical | A. L. Burt & Company | Sequel to Betty Zane 1908 | The Last of the Plainsmen | Western | Outing Publishing | Inspired by Charles \Buffalo\" Jones" 1909 | The Last Trail | Western | Outing Publishing | Sequel to Spirit of the Border 1909 | The ShortStop | Baseball | A. C. McClurg | 1910 | The Heritage of the Desert | Western | Harper & Brothers | 1910 | The Young Forester | Western | Harper & Brothers | 1911 | The Young Pitcher | Baseball | Harper & Brothers | 1911 | The Young Lion Hunter | Western | Harper & Brothers | 1912 | Riders of the Purple Sage | Western | Harper & Brothers | 1912 | Ken Ward in the Jungle | Western | Harper & Brothers | 1913 | Desert Gold | Western | Harper & Brothers | 1914 | The Light of Western Stars | Western | Harper & Brothers | 1915 | The Lone Star Ranger | Western | Harper & Brothers | 1915 | The Rainbow Trail | Western | Harper & Brothers | Sequel to Riders of the Purple Sage 1916 | The Border Legion | Western | Harper & Brothers | 1917 | Wildfire | Western | Harper & Brothers | 1918 | The UP Trail | Western | Harper & Brothers | 1919 | The Desert of Wheat | Western | Harper & Brothers | 1919 | Tales of Fishes | Fishing | Harper & Brothers | 1920 | The Man of the Forest | Western | Grosset & Dunlap | 1920 | The Redheaded Outfield and other Baseball Stories | Baseball | Harper & Brothers | 1921 | The Mysterious Rider | Western | Harper & Brothers | 1921 | To the Last Man | Western | Harper & Brothers | 1922 | The Day of the Beast | Fiction | Harper & Brothers | 1922 | Tales of Lonely Trails | Adventure | Harper & Brothers | 1923 | Wanderer of the Wasteland | Western | Harper & Brothers | 1923 | Tappan's Burro | Western | Harper & Brothers | 1924 | The Call of the Canyon | Western | Harper & Brothers | 1924 | Roping Lions in the Grand Canyon | Adventure | Harper & Brothers | 1924 | Tales of Southern Rivers | Fishing | Harper & Brothers | 1925 | The Thundering Herd | Western | Harper & Brothers | 1925 | The Vanishing American | Western | Harper & Brothers | 1925 | Tales of Fishing Virgin Seas | Fishing | Harper & Brothers | 1926 | Under the Tonto Rim | Western | Harper & Brothers | 1926 | Tales of the Angler's Eldorado, New Zealand | Fishing | Harper & Brothers | 1927 | Forlorn River | Western | Harper & Brothers | 1927 | Tales of Swordfish and Tuna | Fishing | Harper & Brothers | 1928 | Nevada | Western | Harper & Brothers | Sequel to Forlorn River 1928 | Wild Horse Mesa | Western | Harper & Brothers | 1928 | Don, the Story of a Lion Dog | Western | Harper & Brothers | 1928 | Avalanche | Western | Harper & Brothers | 1928 | Tales of Fresh Water Fishing | Fishing | Harper & Brothers | 1929 | Fighting Caravans | Western | Harper & Brothers | 1929 | Stairs of Sand | Western | Harper & Brothers | 1930 | The Wolf Tracker | Western | Harper & Brothers | 1930 | The Shepherd of Guadaloupe | Western | Harper & Brothers | 1931 | Sunset Pass | Western | Harper & Brothers | 1931 | Tales of Tahitian Waters | Fishing | Harper & Brothers | 1931 | Book of Camps and Trails | Adventure | Harper & Brothers | Partial re-print of Tales of Lonely Trails 1932 | Arizona Ames | Western | Harper & Brothers | 1932 | Robbers' Roost | Western | Harper & Brothers | 1933 | The Drift Fence | Western | Harper & Brothers | 1933 | The Hash Knife Outfit | Western | Harper & Brothers | Sequel to The Drift Fence 1934 | The Code of the West | Western | Harper & Brothers | 1935 | Thunder Mountain | Western | Harper & Brothers | 1935 | The Trail Driver | Western | Whitman Publishing | 1936 | The Lost Wagon Train | Western | Harper & Brothers | 1937 | West of the Pecos | Western | Whitman Publishing | 1937 | An American Angler in Australia | Fishing | Whitman Publishing | 1938 | Raiders of Spanish Peaks | Western | Whitman Publishing | 1939 | Western Union | Western | Harper & Brothers | 1939 | Knights of the Range | Western | Harper & Brothers | 1940 | Thirty thousand on the Hoof | Western | Harper & Brothers | 1940 | Twin Sombreros | Western | Harper & Brothers | Sequel to Knights of the Range 1942 | Majesty’s Rancho | Western | Harper & Brothers | Sequel to Light of Western Stars 1943 | Omnibus | Western | Harper & Brothers | 1943 | Stairs of Sand | Western | Harper & Brothers | Sequel to Wanderer of the Wasteland 1944 | The Wilderness Trek | Western | Harper & Brothers | 1946 | Shadow on the Trail | Western | Harper & Brothers | 1947 | Valley of Wild Horses | Western | Harper & Brothers | 1948 | Rogue River Feud | Western | Harper & Brothers | 1949 | The Deer Stalker | Western | Harper & Brothers | 1950 | The Maverick Queen | Western | Harper & Brothers | 1951 | The Dude Ranger | Western | Harper & Brothers | 1952 | Captives of the Desert | Western | Harper & Brothers | 1952 | Adventures in Fishing | Fishing | Harper & Brothers | 1953 | Wyoming | Western | Harper & Brothers | 1954 | Lost Pueblo | Western | Harper & Brothers | 1955 | Black Mesa | Western | Harper & Brothers | 1956 | Stranger from the Tonto | Western | Harper & Brothers | 1957 | The Fugitive Trail | Western | Harper & Brothers | 1958 | Arizona Clan | Western | Harper & Brothers | 1959 | Horse Heaven Hill | Western | Harper & Brothers | 1960 | The Ranger and other Stories | Western | Harper & Row | 1961 | Blue Feather and other Stories | Western | Harper & Row | 1963 | Boulder Dam | Historical | HarperCollins | 1974 | The Adventures of Finspot | Fishing | D-J Books | 1975 | Zane Grey's Greatest Indian Stories | Western | Dorchester Publishing | Includes original ending to The Vanishing American (1925) 1977 | The Reef Girl | Fishing | Harper & Row | 1978 | Tales from a Fisherman’s Log | Fishing | Hodder & Stoughton | 1979 | The Camp Robber and other Stories | Western | Walter J. Black | 1981 | The Lord of Lackawaxen Creek | Adventure | Lime Rock Press | 1982 | Angler's Eldorado: Zane Grey in New Zealand | Fishing | Walter J. Black | Partial reprint of 1926 edition (first 10 chapters, plus additional content) 1994 | George Washington, Frontiersman | Historical | Forge Books | 1996 | Last of the Duanes | Western | Gunsmoke Westerns | Unabridged version of The Lone Star Ranger (1915) 2003 | The Desert Crucible | Western | Leisure Books | Unabridged version of The Rainbow Trail (1915) 2004 | Tonto Basin | Western | Leisure Books | Unabridged version of To the Last Man (1921) 2007 | Shower of Gold | Western | Leisure Books | Unabridged version of Desert Gold (1915) 2008 | The Great Trek | Western | Five Star | Unabridged version of The Wilderness Trek (1944) 2009 | Tales of the Gladiator | Fishing | ZG Collections |
WTQ_for_TSD
Year | Title | Genre | Publisher | Notes 1903 | Betty Zane | Historical | Charles Francis Press | 1906 | Spirit of the Border | Historical | A. L. Burt & Company | Sequel to Betty Zane 1908 | The Last of the Plainsmen | Western | Outing Publishing | Inspired by Charles \Buffalo\" Jones" 1909 | The Last Trail | Western | Outing Publishing | Sequel to Spirit of the Border 1909 | The ShortStop | Baseball | A. C. McClurg | 1910 | The Heritage of the Desert | Western | Harper & Brothers | 1910 | The Young Forester | Western | Harper & Brothers | 1911 | The Young Pitcher | Baseball | Harper & Brothers | 1911 | The Young Lion Hunter | Western | Harper & Brothers | 1912 | Riders of the Purple Sage | Western | Harper & Brothers | 1912 | Ken Ward in the Jungle | Western | Harper & Brothers | 1913 | Desert Gold | Western | Harper & Brothers | 1914 | The Light of Western Stars | Western | Harper & Brothers | 1915 | The Lone Star Ranger | Western | Harper & Brothers | 1915 | The Rainbow Trail | Western | Harper & Brothers | Sequel to Riders of the Purple Sage 1916 | The Border Legion | Western | Harper & Brothers | 1917 | Wildfire | Western | Harper & Brothers | 1918 | The UP Trail | Western | Harper & Brothers | 1919 | The Desert of Wheat | Western | Harper & Brothers | 1919 | Tales of Fishes | Fishing | Harper & Brothers | 1920 | The Man of the Forest | Western | Grosset & Dunlap | 1920 | The Redheaded Outfield and other Baseball Stories | Baseball | Harper & Brothers | 1921 | The Mysterious Rider | Western | Harper & Brothers | 1921 | To the Last Man | Western | Harper & Brothers | 1922 | The Day of the Beast | Fiction | Harper & Brothers | 1922 | Tales of Lonely Trails | Adventure | Harper & Brothers | 1923 | Wanderer of the Wasteland | Western | Harper & Brothers | 1923 | Tappan's Burro | Western | Harper & Brothers | 1924 | The Call of the Canyon | Western | Harper & Brothers | 1924 | Roping Lions in the Grand Canyon | Adventure | Harper & Brothers | 1924 | Tales of Southern Rivers | Fishing | Harper & Brothers | 1925 | The Thundering Herd | Western | Harper & Brothers | 1925 | The Vanishing American | Western | Harper & Brothers | 1925 | Tales of Fishing Virgin Seas | Fishing | Harper & Brothers | 1926 | Under the Tonto Rim | Western | Harper & Brothers | 1926 | Tales of the Angler's Eldorado, New Zealand | Fishing | Harper & Brothers | 1927 | Forlorn River | Western | Harper & Brothers | 1927 | Tales of Swordfish and Tuna | Fishing | Harper & Brothers | 1928 | Nevada | Western | Harper & Brothers | Sequel to Forlorn River 1928 | Wild Horse Mesa | Western | Harper & Brothers | 1928 | Don, the Story of a Lion Dog | Western | Harper & Brothers | 1928 | Avalanche | Western | Harper & Brothers | 1928 | Tales of Fresh Water Fishing | Fishing | Harper & Brothers | 1929 | Fighting Caravans | Western | Harper & Brothers | 1929 | Stairs of Sand | Western | Harper & Brothers | 1930 | The Wolf Tracker | Western | Harper & Brothers | 1930 | The Shepherd of Guadaloupe | Western | Harper & Brothers | 1931 | Sunset Pass | Western | Harper & Brothers | 1931 | Tales of Tahitian Waters | Fishing | Harper & Brothers | 1931 | Book of Camps and Trails | Adventure | Harper & Brothers | Partial re-print of Tales of Lonely Trails 1932 | Arizona Ames | Western | Harper & Brothers | 1932 | Robbers' Roost | Western | Harper & Brothers | 1933 | The Drift Fence | Western | Harper & Brothers | 1933 | The Hash Knife Outfit | Western | Harper & Brothers | Sequel to The Drift Fence 1934 | The Code of the West | Western | Harper & Brothers | 1935 | Thunder Mountain | Western | Harper & Brothers | 1935 | The Trail Driver | Western | Whitman Publishing | 1936 | The Lost Wagon Train | Western | Harper & Brothers | 1937 | West of the Pecos | Western | Whitman Publishing | 1937 | An American Angler in Australia | Fishing | Whitman Publishing | 1938 | Raiders of Spanish Peaks | Western | Whitman Publishing | 1939 | Western Union | Western | Harper & Brothers | 1939 | Knights of the Range | Western | Harper & Brothers | 1940 | Thirty thousand on the Hoof | Western | Harper & Brothers | 1940 | Twin Sombreros | Western | Harper & Brothers | Sequel to Knights of the Range 1942 | Majesty’s Rancho | Western | Harper & Brothers | Sequel to Light of Western Stars 1943 | Omnibus | Western | Harper & Brothers | 1943 | Stairs of Sand | Western | Harper & Brothers | Sequel to Wanderer of the Wasteland 1944 | The Wilderness Trek | Western | Harper & Brothers | 1946 | Shadow on the Trail | Western | Harper & Brothers | 1947 | Valley of Wild Horses | Western | Harper & Brothers | 1948 | Rogue River Feud | Western | Harper & Brothers | 1949 | The Deer Stalker | Western | Harper & Brothers | 1950 | The Maverick Queen | Western | Harper & Brothers | 1951 | The Dude Ranger | Western | Harper & Brothers | 1952 | Captives of the Desert | Western | Harper & Brothers | 1952 | Adventures in Fishing | Fishing | Harper & Brothers | 1953 | Wyoming | Western | Harper & Brothers | 1954 | Lost Pueblo | Western | Harper & Brothers | 1955 | Black Mesa | Western | Harper & Brothers | 1956 | Stranger from the Tonto | Western | Harper & Brothers | 1957 | The Fugitive Trail | Western | Harper & Brothers | 1958 | Arizona Clan | Western | Harper & Brothers | 1959 | Horse Heaven Hill | Western | Harper & Brothers | 1960 | The Ranger and other Stories | Western | Harper & Row | 1961 | Blue Feather and other Stories | Western | Harper & Row | 1963 | Boulder Dam | Historical | HarperCollins | 1974 | The Adventures of Finspot | Fishing | D-J Books | 1975 | Zane Grey's Greatest Indian Stories | Western | Dorchester Publishing | Includes original ending to The Vanishing American (1925) 1977 | The Reef Girl | Fishing | Harper & Row | 1978 | Tales from a Fisherman’s Log | Fishing | Hodder & Stoughton | 1979 | The Camp Robber and other Stories | Western | Walter J. Black | 1981 | The Lord of Lackawaxen Creek | Adventure | Lime Rock Press | 1982 | Angler's Eldorado: Zane Grey in New Zealand | Fishing | Walter J. Black | Partial reprint of 1926 edition (first 10 chapters, plus additional content) 1994 | George Washington, Frontiersman | Historical | Forge Books | 1996 | Last of the Duanes | Western | Gunsmoke Westerns | Unabridged version of The Lone Star Ranger (1915) 2003 | The Desert Crucible | Western | Leisure Books | Unabridged version of The Rainbow Trail (1915) 2004 | Tonto Basin | Western | Leisure Books | Unabridged version of To the Last Man (1921) 2007 | Shower of Gold | Western | Leisure Books | Unabridged version of Desert Gold (1915) 2008 | The Great Trek | Western | Five Star | Unabridged version of The Wilderness Trek (1944) 2009 | Tales of the Gladiator | Fishing | ZG Collections |
Please determine the total count of rows and columns in the provided table, respectively. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_256
WTQ_203-csv_821.jpg
Please determine the total count of rows and columns in the provided table, respectively. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Publication | Country | Accolade | Year | Rank Bill Shapiro | United States | The Top 100 Rock Compact Discs | 1991 | * Blender | United States | The 100 Greatest American Albums of All time | 2002 | 15 Dave Marsh & Kevin Stein | United States | The 40 Best of Album Chartmakers by Year | 1981 | 6 Elvis Costello (Vanity Fair, Issue No. 483) | United States | 500 Albums You Need | 2005 | * Infoplease.com | United States | Must-Have Recordings | 1998 | * Jimmy Guterman | United States | The 100 Best Rock and Roll Records of All Time | 1992 | 27 Kitsap Sun | United States | Top 200 Albums of the Last 40 Years | 2005 | 67 Paul Gambaccini | United States | The World Critics Best Albums of All Time | 1987 | 84 The Recording Academy | United States | Grammy Hall of Fame Albums and Songs | 2004 | * Robert Dimery | United States | 1001 Albums You Must Hear Before You Die | 2005 | * Rolling Stone (Steve Pond) | United States | Steve Pond's 50 (+27) Essential Albums of the 70s | 1990 | 39 Rolling Stone | United States | The 500 Greatest Albums of All Time | 2003 | 165 Vibe | United States | 51 Albums representing a Generation, a Sound and a Movement | 2004 | * Hot Press | Ireland | The 100 Best Albums of All Time | 1989 | 32 Mojo | United Kingdom | Mojo 1000, the Ultimate CD Buyers Guide | 2001 | * NME | United Kingdom | All Times Top 100 Albums | 1985 | 46 NME | United Kingdom | All Times Top 100 Albums + Top 50 by Decade | 1993 | 145 The New Nation | United Kingdom | Top 100 Albums by Black Artists | 2005 | 27 Sounds | United Kingdom | The 100 Best Albums of All Time | 1986 | 24 The Times | United Kingdom | The 100 Best Albums of All Time | 1993 | 58 Time Out | United Kingdom | The 100 Best Albums of All Time | 1989 | 3 The Wire | United Kingdom | The 100 Most Important Records Ever Made | 1992 | * Adresseavisen | Norway | The 100 (+23) Best Albums of All Time | 1995 | 101 Pop | Sweden | The World's 100 Best Albums + 300 Complements | 1994 | 101 OOR | Netherlands | Albums of the Year | 1973 | 41 VPRO | Netherlands | 299 Nominations of the Best Album of All Time | 2006 | * Spex | Germany | The 100 Albums of the Century | 1999 | 93 Rock de Lux | Spain | The 100 Best Albums of the 1970s | 1988 | 39 Rock de Lux | Spain | The 200 Best Albums of All Time | 2002 | 53
WTQ_for_TSD
Publication | Country | Accolade | Year | Rank Bill Shapiro | United States | The Top 100 Rock Compact Discs | 1991 | * Blender | United States | The 100 Greatest American Albums of All time | 2002 | 15 Dave Marsh & Kevin Stein | United States | The 40 Best of Album Chartmakers by Year | 1981 | 6 Elvis Costello (Vanity Fair, Issue No. 483) | United States | 500 Albums You Need | 2005 | * Infoplease.com | United States | Must-Have Recordings | 1998 | * Jimmy Guterman | United States | The 100 Best Rock and Roll Records of All Time | 1992 | 27 Kitsap Sun | United States | Top 200 Albums of the Last 40 Years | 2005 | 67 Paul Gambaccini | United States | The World Critics Best Albums of All Time | 1987 | 84 The Recording Academy | United States | Grammy Hall of Fame Albums and Songs | 2004 | * Robert Dimery | United States | 1001 Albums You Must Hear Before You Die | 2005 | * Rolling Stone (Steve Pond) | United States | Steve Pond's 50 (+27) Essential Albums of the 70s | 1990 | 39 Rolling Stone | United States | The 500 Greatest Albums of All Time | 2003 | 165 Vibe | United States | 51 Albums representing a Generation, a Sound and a Movement | 2004 | * Hot Press | Ireland | The 100 Best Albums of All Time | 1989 | 32 Mojo | United Kingdom | Mojo 1000, the Ultimate CD Buyers Guide | 2001 | * NME | United Kingdom | All Times Top 100 Albums | 1985 | 46 NME | United Kingdom | All Times Top 100 Albums + Top 50 by Decade | 1993 | 145 The New Nation | United Kingdom | Top 100 Albums by Black Artists | 2005 | 27 Sounds | United Kingdom | The 100 Best Albums of All Time | 1986 | 24 The Times | United Kingdom | The 100 Best Albums of All Time | 1993 | 58 Time Out | United Kingdom | The 100 Best Albums of All Time | 1989 | 3 The Wire | United Kingdom | The 100 Most Important Records Ever Made | 1992 | * Adresseavisen | Norway | The 100 (+23) Best Albums of All Time | 1995 | 101 Pop | Sweden | The World's 100 Best Albums + 300 Complements | 1994 | 101 OOR | Netherlands | Albums of the Year | 1973 | 41 VPRO | Netherlands | 299 Nominations of the Best Album of All Time | 2006 | * Spex | Germany | The 100 Albums of the Century | 1999 | 93 Rock de Lux | Spain | The 100 Best Albums of the 1970s | 1988 | 39 Rock de Lux | Spain | The 200 Best Albums of All Time | 2002 | 53
Please determine the total count of rows and columns in the provided table, respectively. The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_257
WTQ_203-csv_143.jpg
Tell me how many rows and columns exist in the given table. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Date | Opponent | Venue | Result | Attendance | Scorers 13 August 2005 | Charlton Athletic | Stadium of Light | 1–3 | 34,446 | Gray 20 August 2005 | Liverpool | Anfield | 0–1 | 44,913 | 23 August 2005 | Manchester City | Stadium of Light | 1–2 | 33,357 | Le Tallec 27 August 2005 | Wigan Athletic | JJB Stadium | 0–1 | 17,223 | 10 September 2005 | Chelsea | Stamford Bridge | 0–2 | 41,969 | 17 September 2005 | West Bromwich Albion | Stadium of Light | 1–1 | 31,657 | Breen 25 September 2005 | Middlesbrough | Riverside Stadium | 2–0 | 29,583 | Miller, Arca 1 October 2005 | West Ham United | Stadium of Light | 1–1 | 31,212 | Miller 15 October 2005 | Manchester United | Stadium of Light | 1–3 | 39,085 | Elliott 23 October 2005 | Newcastle United | St James' Park | 2–3 | 52,302 | Lawrence, Elliott 29 October 2005 | Portsmouth | Stadium of Light | 1–4 | 34,926 | Whitehead (pen) 5 November 2005 | Arsenal | Highbury | 1–3 | 38,210 | Stubbs 19 November 2005 | Aston Villa | Stadium of Light | 1–3 | 39,707 | Whitehead (pen) 26 November 2005 | Birmingham City | Stadium of Light | 0–1 | 32,442 | 30 November 2005 | Liverpool | Stadium of Light | 0–2 | 32,697 | 3 December 2005 | Tottenham Hotspur | White Hart Lane | 2–3 | 36,244 | Whitehead, Le Tallec 10 December 2005 | Charlton Athletic | The Valley | 0–2 | 26,065 | 26 December 2005 | Bolton Wanderers | Stadium of Light | 0–0 | 32,232 | 31 December 2005 | Everton | Stadium of Light | 0–1 | 30,567 | 2 January 2006 | Fulham | Craven Cottage | 1–2 | 19,372 | Lawrence 15 January 2006 | Chelsea | Stadium of Light | 1–2 | 32,420 | Lawrence 21 January 2006 | West Bromwich Albion | The Hawthorns | 1–0 | 26,464 | Watson (own goal) 31 January 2006 | Middlesbrough | Stadium of Light | 0–3 | 31,675 | 4 February 2006 | West Ham United | Boleyn Ground | 0–2 | 34,745 | 12 February 2006 | Tottenham Hotspur | Stadium of Light | 1–1 | 34,700 | Murphy 15 February 2006 | Blackburn Rovers | Ewood Park | 0–2 | 18,220 | 25 February 2006 | Birmingham City | St. Andrew's | 0–1 | 29,257 | 3 March 2006 | Manchester City | City of Manchester Stadium | 1–2 | 42,200 | Kyle 11 March 2006 | Wigan Athletic | Stadium of Light | 0–1 | 31,194 | 18 March 2006 | Bolton Wanderers | Reebok Stadium | 0–2 | 23,568 | 25 March 2006 | Blackburn Rovers | Stadium of Light | 0–1 | 29,593 | 1 April 2006 | Everton | Goodison Park | 2–2 | 38,093 | Stead, Delap 14 April 2006 | Manchester United | Old Trafford | 0–0 | 72,519 | 17 April 2006 | Newcastle United | Stadium of Light | 1–4 | 40,032 | Hoyte 22 April 2006 | Portsmouth | Fratton Park | 1–2 | 20,078 | Miller 1 May 2006 | Arsenal | Stadium of Light | 0–3 | 44,003 | 4 May 2006 | Fulham | Stadium of Light | 2–1 | 28,226 | Le Tallec, Brown 7 May 2006 | Aston Villa | Villa Park | 1–2 | 33,820 | D. Collins
WTQ_for_TSD
Date | Opponent | Venue | Result | Attendance | Scorers 13 August 2005 | Charlton Athletic | Stadium of Light | 1–3 | 34,446 | Gray 20 August 2005 | Liverpool | Anfield | 0–1 | 44,913 | 23 August 2005 | Manchester City | Stadium of Light | 1–2 | 33,357 | Le Tallec 27 August 2005 | Wigan Athletic | JJB Stadium | 0–1 | 17,223 | 10 September 2005 | Chelsea | Stamford Bridge | 0–2 | 41,969 | 17 September 2005 | West Bromwich Albion | Stadium of Light | 1–1 | 31,657 | Breen 25 September 2005 | Middlesbrough | Riverside Stadium | 2–0 | 29,583 | Miller, Arca 1 October 2005 | West Ham United | Stadium of Light | 1–1 | 31,212 | Miller 15 October 2005 | Manchester United | Stadium of Light | 1–3 | 39,085 | Elliott 23 October 2005 | Newcastle United | St James' Park | 2–3 | 52,302 | Lawrence, Elliott 29 October 2005 | Portsmouth | Stadium of Light | 1–4 | 34,926 | Whitehead (pen) 5 November 2005 | Arsenal | Highbury | 1–3 | 38,210 | Stubbs 19 November 2005 | Aston Villa | Stadium of Light | 1–3 | 39,707 | Whitehead (pen) 26 November 2005 | Birmingham City | Stadium of Light | 0–1 | 32,442 | 30 November 2005 | Liverpool | Stadium of Light | 0–2 | 32,697 | 3 December 2005 | Tottenham Hotspur | White Hart Lane | 2–3 | 36,244 | Whitehead, Le Tallec 10 December 2005 | Charlton Athletic | The Valley | 0–2 | 26,065 | 26 December 2005 | Bolton Wanderers | Stadium of Light | 0–0 | 32,232 | 31 December 2005 | Everton | Stadium of Light | 0–1 | 30,567 | 2 January 2006 | Fulham | Craven Cottage | 1–2 | 19,372 | Lawrence 15 January 2006 | Chelsea | Stadium of Light | 1–2 | 32,420 | Lawrence 21 January 2006 | West Bromwich Albion | The Hawthorns | 1–0 | 26,464 | Watson (own goal) 31 January 2006 | Middlesbrough | Stadium of Light | 0–3 | 31,675 | 4 February 2006 | West Ham United | Boleyn Ground | 0–2 | 34,745 | 12 February 2006 | Tottenham Hotspur | Stadium of Light | 1–1 | 34,700 | Murphy 15 February 2006 | Blackburn Rovers | Ewood Park | 0–2 | 18,220 | 25 February 2006 | Birmingham City | St. Andrew's | 0–1 | 29,257 | 3 March 2006 | Manchester City | City of Manchester Stadium | 1–2 | 42,200 | Kyle 11 March 2006 | Wigan Athletic | Stadium of Light | 0–1 | 31,194 | 18 March 2006 | Bolton Wanderers | Reebok Stadium | 0–2 | 23,568 | 25 March 2006 | Blackburn Rovers | Stadium of Light | 0–1 | 29,593 | 1 April 2006 | Everton | Goodison Park | 2–2 | 38,093 | Stead, Delap 14 April 2006 | Manchester United | Old Trafford | 0–0 | 72,519 | 17 April 2006 | Newcastle United | Stadium of Light | 1–4 | 40,032 | Hoyte 22 April 2006 | Portsmouth | Fratton Park | 1–2 | 20,078 | Miller 1 May 2006 | Arsenal | Stadium of Light | 0–3 | 44,003 | 4 May 2006 | Fulham | Stadium of Light | 2–1 | 28,226 | Le Tallec, Brown 7 May 2006 | Aston Villa | Villa Park | 1–2 | 33,820 | D. Collins
Tell me how many rows and columns exist in the given table. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_258
WTQ_203-csv_453.jpg
How many rows and columns does this table have? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Type | Construction period | Cylinder | Capacity | Power | Vmax 10 PS (7 kW; 10 hp) | 1901–1902 | straight-2 | 1.527 cc | 18 PS (13,2 kW) | 50 km/h (31 mph) 8/14 PS | 1902–1905 | straight-2 | 1.527 cc | 14 PS (10,3 kW) | 50 km/h (31 mph) 20 PS (15 kW; 20 hp) | 1904–1905 | straight-4 | 7.946 cc | 45 PS (33 kW) | 85 km/h (53 mph) P4 (11/22 PS) | 1905–1910 | straight-4. | 3.054 cc | 22 PS (16,2 kW) | 70 km/h (43 mph) P2 (9/12 PS) | 1906–1907 | straight-2 | 2.281 cc | 16 PS (11,8 kW) | 55 km/h (34 mph) P4-1 (24/36 PS) | 1906–1910 | straight-4 | 5.880 cc | 40 PS (29 kW) | 80 km/h (50 mph) P6 (34/60 PS) | 1906–1911 | straight-6 | 8.820 cc | 60 PS (44 kW) | 95 km/h (59 mph) G4 (6/12 PS) | 1907–1911 | straight-4 | 1.500 cc | 12 PS (8,8 kW) | 60 km/h (37 mph) PK4 (11/20 PS) | 1909–1912 | straight-4 | 2.544 cc | 20 PS (14,7 kW) | 70 km/h (43 mph) C1 (6/18 PS) | 1909–1915 | straight-4 | 1.546 cc | 18 PS (13,2 kW) | 70 km/h (43 mph) B1 (6/16 PS) | 1910–1912 | straight-4 | 1.556 cc | 16 PS (11,8 kW) | 65 km/h (40 mph) B6 (9/22 PS) | 1912–1914 | straight-4 | 4.900 cc | 45 PS (33 kW) | 95 km/h (59 mph) C2 (10/28 PS) | 1913–1914 | straight-4 | 2.412 cc | 28 PS (20,6 kW) | 75 km/h (47 mph) C5 (6/18 PS) | 1915–1919 | straight-4 | 1.546 cc | 15 PS (11 kW) | 70 km/h (43 mph) D2 (6/18 PS) | 1919–1920 | straight-4 | 1.593 cc | 18 PS (13,2 kW) | 70 km/h (43 mph) D6 (19/55 PS) | 1919–1921 | straight-6 | 4.960 cc | 55 PS (40 kW) | 100 km/h (62 mph) D7 (42/120 PS) | 1919–1921 | straight-6 | 11.160 cc | 120 PS (88 kW) | 160 km/h (99 mph) D3 (8/24 PS) | 1920–1923 | straight-4 | 2.120 cc | 24 PS (17,6 kW) | 70 km/h (43 mph) D5 (12/36 PS) | 1920–1923 | straight-6 | 3.107 cc | 36 PS (26,5 kW) | 80 km/h (50 mph) D9 (8/32 PS) | 1923–1924 | straight-4 | 2.290 cc | 32 PS (23,5 kW) | 90 km/h (56 mph) D12 (12/45 PS) | 1923–1924 | straight-6 | 3.107 cc | 45 PS (33 kW) | 100 km/h (62 mph) D10 (10/50 PS) | 1924–1925 | straight-4 | 2.580 cc | 50 PS (37 kW) | 120 km/h (75 mph) D9V (9/32 PS) | 1925–1927 | straight-4 | 2.290 cc | 32 PS (23,5 kW) | 90 km/h (56 mph) D12V (13/55 PS) | 1925–1928 | straight-6 | 3.386 cc | 55 PS (40 kW) | 100 km/h (62 mph) F6 (6/30 PS) | 1927–1928 | straight-4 | 1.570 cc | 30 PS (22 kW) | 70 km/h (43 mph) 8 Typ S 8 (8/45 PS) | 1928 | straight-8 | 1.999 cc | 45 PS (33 kW) | 85 km/h (53 mph) 8 Typ G 14 (14/70 PS) | 1928 | straight-8 | 3.633 cc | 70 PS (51 kW) | 100 km/h (62 mph) 8 Typ S 10 (10/50 PS) | 1928–1930 | straight-8 | 2.464 cc | 50 PS (37 kW) | 90 km/h (56 mph) Gigant G 15 K (15/80 PS) | 1928–1933 | straight-8 | 3.974 cc | 80 PS (59 kW) | 110 km/h (68 mph) Gigant G 15 (15/80 PS) | 1928–1933 | straight-8 | 3.974 cc | 80 PS (59 kW) | 100 km/h (62 mph) Repräsentant P 20 (20/100 PS) | 1930–1933 | straight-8 | 4.906 cc | 100 PS (74 kW) | 120 km/h (75 mph) Marschall M 12 (12/60 PS) | 1930–1934 | straight-8 | 2.963 cc | 60 PS (44 kW) | 90 km/h (56 mph) V 5 | 1931–1932 | V4 | 1.168 cc | 25 PS (18,4 kW) | 80 km/h (50 mph) V 5 Sport | 1931–1932 | V4 | 1.168 cc | 30 PS (22 kW) | 100 km/h (62 mph) R 140 | 1932–1933 | straight-4 | 1.355 cc | 30 PS (22 kW) | 85 km/h (53 mph)–105 km/h (65 mph) R 140 | 1933–1934 | straight-4 | 1.466 cc | 30 PS (22 kW) | 85 km/h (53 mph)–105 km/h (65 mph) R 150 | 1934–1935 | straight-4 | 1.466 cc | 35 PS (25,7 kW) | 90–110 km/h Greif V8 | 1934–1937 | V8 | 2.489 cc | 55 PS (40 kW) | 110 km/h (68 mph) R 180 | 1935 | straight-4 | 1.769 cc | 45 PS (33 kW) | 105 km/h (65 mph) Greif V8 Sport | 1935–1937 | V8 | 2.489 cc | 57 PS (42 kW) | 120 km/h (75 mph) Greif Junior | 1936–1939 | flat-4 | 1.484 cc | 34 PS (25 kW) | 100 km/h (62 mph) Sedina | 1937–1940 | straight-4 | 2.406 cc | 55 PS (40 kW) | 110 km/h (68 mph) Arkona | 1937–1940 | straight-6 | 3.610 cc | 80 PS (59 kW) | 120 km/h (75 mph)–140 km/h (87 mph)
WTQ_for_TSD
Type | Construction period | Cylinder | Capacity | Power | Vmax 10 PS (7 kW; 10 hp) | 1901–1902 | straight-2 | 1.527 cc | 18 PS (13,2 kW) | 50 km/h (31 mph) 8/14 PS | 1902–1905 | straight-2 | 1.527 cc | 14 PS (10,3 kW) | 50 km/h (31 mph) 20 PS (15 kW; 20 hp) | 1904–1905 | straight-4 | 7.946 cc | 45 PS (33 kW) | 85 km/h (53 mph) P4 (11/22 PS) | 1905–1910 | straight-4. | 3.054 cc | 22 PS (16,2 kW) | 70 km/h (43 mph) P2 (9/12 PS) | 1906–1907 | straight-2 | 2.281 cc | 16 PS (11,8 kW) | 55 km/h (34 mph) P4-1 (24/36 PS) | 1906–1910 | straight-4 | 5.880 cc | 40 PS (29 kW) | 80 km/h (50 mph) P6 (34/60 PS) | 1906–1911 | straight-6 | 8.820 cc | 60 PS (44 kW) | 95 km/h (59 mph) G4 (6/12 PS) | 1907–1911 | straight-4 | 1.500 cc | 12 PS (8,8 kW) | 60 km/h (37 mph) PK4 (11/20 PS) | 1909–1912 | straight-4 | 2.544 cc | 20 PS (14,7 kW) | 70 km/h (43 mph) C1 (6/18 PS) | 1909–1915 | straight-4 | 1.546 cc | 18 PS (13,2 kW) | 70 km/h (43 mph) B1 (6/16 PS) | 1910–1912 | straight-4 | 1.556 cc | 16 PS (11,8 kW) | 65 km/h (40 mph) B6 (9/22 PS) | 1912–1914 | straight-4 | 4.900 cc | 45 PS (33 kW) | 95 km/h (59 mph) C2 (10/28 PS) | 1913–1914 | straight-4 | 2.412 cc | 28 PS (20,6 kW) | 75 km/h (47 mph) C5 (6/18 PS) | 1915–1919 | straight-4 | 1.546 cc | 15 PS (11 kW) | 70 km/h (43 mph) D2 (6/18 PS) | 1919–1920 | straight-4 | 1.593 cc | 18 PS (13,2 kW) | 70 km/h (43 mph) D6 (19/55 PS) | 1919–1921 | straight-6 | 4.960 cc | 55 PS (40 kW) | 100 km/h (62 mph) D7 (42/120 PS) | 1919–1921 | straight-6 | 11.160 cc | 120 PS (88 kW) | 160 km/h (99 mph) D3 (8/24 PS) | 1920–1923 | straight-4 | 2.120 cc | 24 PS (17,6 kW) | 70 km/h (43 mph) D5 (12/36 PS) | 1920–1923 | straight-6 | 3.107 cc | 36 PS (26,5 kW) | 80 km/h (50 mph) D9 (8/32 PS) | 1923–1924 | straight-4 | 2.290 cc | 32 PS (23,5 kW) | 90 km/h (56 mph) D12 (12/45 PS) | 1923–1924 | straight-6 | 3.107 cc | 45 PS (33 kW) | 100 km/h (62 mph) D10 (10/50 PS) | 1924–1925 | straight-4 | 2.580 cc | 50 PS (37 kW) | 120 km/h (75 mph) D9V (9/32 PS) | 1925–1927 | straight-4 | 2.290 cc | 32 PS (23,5 kW) | 90 km/h (56 mph) D12V (13/55 PS) | 1925–1928 | straight-6 | 3.386 cc | 55 PS (40 kW) | 100 km/h (62 mph) F6 (6/30 PS) | 1927–1928 | straight-4 | 1.570 cc | 30 PS (22 kW) | 70 km/h (43 mph) 8 Typ S 8 (8/45 PS) | 1928 | straight-8 | 1.999 cc | 45 PS (33 kW) | 85 km/h (53 mph) 8 Typ G 14 (14/70 PS) | 1928 | straight-8 | 3.633 cc | 70 PS (51 kW) | 100 km/h (62 mph) 8 Typ S 10 (10/50 PS) | 1928–1930 | straight-8 | 2.464 cc | 50 PS (37 kW) | 90 km/h (56 mph) Gigant G 15 K (15/80 PS) | 1928–1933 | straight-8 | 3.974 cc | 80 PS (59 kW) | 110 km/h (68 mph) Gigant G 15 (15/80 PS) | 1928–1933 | straight-8 | 3.974 cc | 80 PS (59 kW) | 100 km/h (62 mph) Repräsentant P 20 (20/100 PS) | 1930–1933 | straight-8 | 4.906 cc | 100 PS (74 kW) | 120 km/h (75 mph) Marschall M 12 (12/60 PS) | 1930–1934 | straight-8 | 2.963 cc | 60 PS (44 kW) | 90 km/h (56 mph) V 5 | 1931–1932 | V4 | 1.168 cc | 25 PS (18,4 kW) | 80 km/h (50 mph) V 5 Sport | 1931–1932 | V4 | 1.168 cc | 30 PS (22 kW) | 100 km/h (62 mph) R 140 | 1932–1933 | straight-4 | 1.355 cc | 30 PS (22 kW) | 85 km/h (53 mph)–105 km/h (65 mph) R 140 | 1933–1934 | straight-4 | 1.466 cc | 30 PS (22 kW) | 85 km/h (53 mph)–105 km/h (65 mph) R 150 | 1934–1935 | straight-4 | 1.466 cc | 35 PS (25,7 kW) | 90–110 km/h Greif V8 | 1934–1937 | V8 | 2.489 cc | 55 PS (40 kW) | 110 km/h (68 mph) R 180 | 1935 | straight-4 | 1.769 cc | 45 PS (33 kW) | 105 km/h (65 mph) Greif V8 Sport | 1935–1937 | V8 | 2.489 cc | 57 PS (42 kW) | 120 km/h (75 mph) Greif Junior | 1936–1939 | flat-4 | 1.484 cc | 34 PS (25 kW) | 100 km/h (62 mph) Sedina | 1937–1940 | straight-4 | 2.406 cc | 55 PS (40 kW) | 110 km/h (68 mph) Arkona | 1937–1940 | straight-6 | 3.610 cc | 80 PS (59 kW) | 120 km/h (75 mph)–140 km/h (87 mph)
How many rows and columns does this table have? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_259
WTQ_203-csv_50.jpg
What is the count of rows and columns in the given table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> # | Date | Venue | Opponent | Score | Result | Competition 1 | April 4, 1985 | Portland, Oregon | Canada | N/A | 1–1 | Friendly 2 | August 13, 1988 | St. Louis, Missouri | Jamaica | 2–1 | 5-1 | 1990 World Cup qualifying 3 | September 17, 1989 | Tegucigalpa, Honduras | El Salvador | 1–0 | 1–0 | 1990 World Cup qualifying 4 | July 3, 1991 | Los Angeles, California | Costa Rica | 2–2 | 3–2 | 1991 CONCACAF Gold Cup 5 | March 18, 1992 | Casablanca, Morocco | Morocco | 1–2 | 1–3 | Friendly 6 | April 4, 1992 | Palo Alto, California | China PR | 1–0 | 1-0 | Friendly 7 | April 4, 1992 | Palo Alto, California | China PR | 5–0 | 1-0 | Friendly 8 | March 14, 1993 | Tokyo, Japan | Japan | 1–0 | 1–3 | Friendly 9 | October 16, 1993 | High Point, North Carolina | Ukraine | 1–0 | 1–2 | Friendly 10 | December 5, 1993 | Los Angeles, California | El Salvador | 5–0 | 7–0 | Friendly 11 | February 20, 1994 | Miami, Florida | Sweden | 1–3 | 1–0 | Friendly 12 | March 26, 1994 | Dallas, Texas | Bolivia | 1–1 | 2–2 | Friendly
WTQ_for_TSD
# | Date | Venue | Opponent | Score | Result | Competition 1 | April 4, 1985 | Portland, Oregon | Canada | N/A | 1–1 | Friendly 2 | August 13, 1988 | St. Louis, Missouri | Jamaica | 2–1 | 5-1 | 1990 World Cup qualifying 3 | September 17, 1989 | Tegucigalpa, Honduras | El Salvador | 1–0 | 1–0 | 1990 World Cup qualifying 4 | July 3, 1991 | Los Angeles, California | Costa Rica | 2–2 | 3–2 | 1991 CONCACAF Gold Cup 5 | March 18, 1992 | Casablanca, Morocco | Morocco | 1–2 | 1–3 | Friendly 6 | April 4, 1992 | Palo Alto, California | China PR | 1–0 | 1-0 | Friendly 7 | April 4, 1992 | Palo Alto, California | China PR | 5–0 | 1-0 | Friendly 8 | March 14, 1993 | Tokyo, Japan | Japan | 1–0 | 1–3 | Friendly 9 | October 16, 1993 | High Point, North Carolina | Ukraine | 1–0 | 1–2 | Friendly 10 | December 5, 1993 | Los Angeles, California | El Salvador | 5–0 | 7–0 | Friendly 11 | February 20, 1994 | Miami, Florida | Sweden | 1–3 | 1–0 | Friendly 12 | March 26, 1994 | Dallas, Texas | Bolivia | 1–1 | 2–2 | Friendly
What is the count of rows and columns in the given table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_260
WTQ_203-csv_738.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Common name | Binomial nomenclature | Colour | Density ¹ | Location | Characteristics, Usage and Status Aini or Aangili | Artocarpus hirsutus | Yellowish brown | 595 kg/m³ | Maharashtra, Andhra Pradesh, Tamil Nadu, Karnataka, Kerala | Elastic, close-grained, and strong. It takes polish. It can be used underwater. It is used for ordinary building construction, structural work, paving, furniture and so forth. Arjun | Terminalia arjuna Terminalia elliptica | Dark brown | 870 kg/m³ | Central India | It is heavy and strong. It has such uses as beams, rafters, and posts. Axlewood | Anogeissus latifolia | | 930 kg/m³ | Andhra Pradesh, Tamil Nadu, Maharashtra, Madhya Pradesh, Bihar, Uttar Pradesh | It is very strong, hard and tough. It takes a smooth finish. It is subject to cracking. Babul | Acacia nilotica subsp. indica | Whitish red | 835 kg/m³ | Rajasthan, Andhra Pradesh, Maharashtra, Madhya Pradesh, Tamil Nadu, Karnataka, Bengal, Gujarat, Uttar Pradesh | It is strong, hard and tough and it takes up a good polish. It is used for such products as bodies and wheels of bullock cart, agricultural instruments, tool handles, and well curbs. Bakul | Mimusops elengi Mimusops parvifolia | Reddish brown | 880 kg/m³ | Some parts of North India | It is close-grained and tough. It is used for making cabinets. Bamboo | Family Poaceae, tribe Bambuseae | | | Throughout India, especially Assam and Bengal | Not actually a tree, but a woody grass, it is flexible, very strong and durable. It is used for scaffoldings, thatched roofs, rafters, temporary bridges, and so forth. Banyan | Ficus benghalensis | Brown | 580 kg/m³ | Throughout India | It is strong and durable only under water. The aerial roots are utilized for such items as tent poles and well curbs. Benteak | Lagerstoemia parviflora | | 675 kg/m³ | Kerala, Madras, Maharashtra, Karnataka | It is strong and takes up a smooth surface. It may be used for building constructions, boat building and furniture. Bijasal | Pterocarpus marsupium | Light brown | 800 kg/m³ | Karnataka, Andhra Pradesh, Madhya Pradesh, Maharashtra, Kerala, Uttar Pradesh, Tamil Nadu, Orissa | It is coarse-grained, durable and strong but difficult to work. Termites (also known as white ant) do not easily attack it. It is used for ordinary building construction and for cart wheels. Vulnerable Casuarina | Casuarina spp. | Reddish brown | 765 kg/m³ | Andhra Pradesh, Tamil Nadu | It grows straight. It is strong and fibrous. It is, however, badly twisted. It is often used for scaffolding and posts for temporary structures. Coconut | Cocos nucifera | Reddish brown | | Throughout coastal India | Takes polish. Requires preservative treatment. Used as poles, piles, furniture and as formwork in concrete construction. Deodar | Cedrus deodara | Yellowish brown | 560 kg/m³ | Himalayas, Punjab, Uttar Pradesh | Deodar is the most important timber tree providing soft wood. It can be easily worked and it is moderately strong. It possesses distinct annual rings. It is used for making cheap furniture, railway carriages, railway sleepers, packing boxes, structural work and so forth. Gambar | Gmelina arborea | Pale yellow | 580 kg/m³ | Central India, South India | It can be easily worked and is strong and durable especially when used under water. It is used for such products as furniture, carriage, well curbs, yokes, and door panels. Hopea | Hopea parviflora | Light to deep brown | 1010 kg/m³ | Madras, Kerala | Hopea is extremely strong and tough. It is difficult to work. However, it can be seasoned easily and it is durable and not likely to be damaged by white ants. It has been variously used for ordinary house construction, railway sleepers, piles, and boat building. Endangered Himalayan Elm, Indian Elm | Ulmus wallichiana | Red | 960 kg/m³ | Throughout India | It is moderately hard and strong. It is used for door and window frames, carts, and so forth. Ironwood, Penaga Lilin, Bosneak, Gangaw, Mesua | Mesua ferrea | Reddish brown | 960–1060 kg/m³ | | Ironwood is durable though it is very hard and is not easily worked. It even resists penetration of nails. It is used for ordinary house construction, bridges, piles, agricultural instruments, railway wagons, and railway sleepers. Irul, Pyinkado | Xylia xylocarpa | | 830–1060 kg/m³ | Karnataka, Kerala, Andhra Pradesh, Maharashtra, Orissa, Tamil Nadu | It is very hard, heavy and durable. Difficult to work, it also requires slow and careful seasoning. It is used for railway sleepers, agricultural instruments, paving blocks, and heavy construction. Least concern Jack | Mangifera caesia. | Yellow, darkens with age | 595 kg/m³ | Karnataka, Maharashtra, Tamil Nadu, Kerala | It is compact and even grained. It is moderately strong and easy to work. It takes a good finish and maintains its shape well. It has many uses including plain furniture, boat construction, well curbs, door panels, cabinet making and musical instruments. Jarul | Lagerstroemia flos-reginae | Light reddish gray | 640 kg/m³ | Assam, Bengal, Maharashtra | Hard and durable, it can be easily worked. It takes a good finish and is used for house construction, boat building, railway carriages, cart making and scaffolding. Kathal, Keledang, Jackfruit | Artocarpus heterophyllus | Yellow to deep brown | 800 kg/m³ | Karnataka, Andhra Pradesh, Kerala, Maharashtra, Tamil Nadu | It is heavy and hard. It is durable under water and in damp conditions, however, it cracks if exposed to direct sun. White ants do not attack it. It is used for piles, platforms of wooden bridges, door and window panels. Lauraceae, Saj | Lauraceae | Dark brown | 880 kg/m³ | Karnataka, Andhra Pradesh, Bihar, Orissa, Madhya Pradesh, Kerala, Tamil Nadu | It is strong, hard and tough. It is subject to cracking and attack by dry rot. White ants do not attack it. It takes a smooth finish. It is used for such purposes as house construction, boat construction, railway sleepers and structural work. Mahogany | Swietenia spp. | Reddish brown | 720 kg/m³ | | It takes a good polish and is easily worked. It is durable under water. It is most commonly used for furniture, pattern making and cabinet work. Mango | Mangifera spp | Deep gray | 560–720 kg/m³ | Throughout India | The mango tree is well known for its fruits. It is easy to work and it maintains its shape well. It is moderately strong. It is most often used for cheap furniture, toys, packing boxes, cabinet work, panels for doors and for windows. Mulberry | Morus spp. | Brown | 650 kg/m³ | Punjab | It is strong, tough and elastic. It takes up a clean finish. It can be well seasoned. It is turned and carved easily. Mulberry is typically used for baskets and sports goods like hockey sticks, tennis rackets and cricket bats. Oak | Quercus spp. | Yellowish brown | 865 kg/m³ | | Oak is strong and durable, with straight silvery grain. It is used for preparing sporting goods. Palm | Arecaceae | Dark brown | 1040 kg/m³ | Throughout India | It contains ripe wood in the outer crust. The colour of this ripened wood is dark brown. It is strong, durable and fibrous. Palm is used for furniture, roof covering, rafters and joists. Pine | Pinus spp. | | | | Pine wood is hard and tough except white pine which is soft. It decays easily if it comes into contact with soil. It is heavy and coarse grained. It is used for pattern making, frames for doors and windows, and for paving material. White pine is light and straight grained and is used in the manufacture of matches. Red cedar | | Red | 480 kg/m³ | Assam, Nagpur | It is soft and even grained. It is used for furniture, door panels and well curbs. Rosewood | Dalbergia latifolia | Dark | 850 kg/m³ | Kerala, Karnataka, Maharashtra, Madhya Pradesh, Tamil Nadu, Orrissa | It is strong, tough and close-grained. It is a handsome wood that takes up a high polish. It maintains its shape well and is available in large sizes. It is used for furniture of superior quality, cabinet work, ornamental carvings and so forth. Vulnerable Sal | Shorea robusta | Brown | 880–1050 kg/m³ | Karnataka, Andhra Pradesh, Maharashtra, Uttar Pradesh, Bihar, Madhya Pradesh, Orissa | It is hard, fibrous and close-grained. It does not take up a good polish. It requires slow and careful seasoning. It is durable under ground and water. It is used for railway sleepers, shipbuilding, and bridges. Sandalwood | Santalum spp. | White or Red | 930 kg/m³ | Karnataka, Tamil Nadu, Kerala, Assam, Nagpur, Bengal | It has a pleasant smell. It is commonly used for agricultural instruments, well curbs, wheels, and mallets. Vulnerable Satinwood | Chloroxylon swietenia | Yellow | 960 kg/m³ | Central and Southern India | It is very hard and durable. It is close grained. It is used for furniture and other ornamental works. Vulnerable Simul | Bombax spp. | White | 450 kg/m³ | All over India | It is a loose grained, inferior quality wood. Light in weight, it is used for packing cases, the match industry, well curbs, and for cheap furniture. Siris | Albizia spp. | Dark brown | | North India | Hard and durable, Siris wood is difficult to work. It is used for well curbs in salty water, beams, posts, and furniture. Sissoo | Dalbergia sissoo | Dark brown | 770 kg/m³ | Mysore, Maharashtra, Assam, Bengal, Uttar Pradesh, Orissa | Also known as shisham or tali, this wood is strong and tough. It is durable and handsome and it maintains its shape well. It can be easily seasoned. It is difficult to work but it takes a fine polish. It is used for high quality furniture, plywoods, bridge piles, sport goods, railway sleepers and so forth. It is a very good material for decorative works and carvings. Spruce | Picea spp. | | 480 kg/m³ | | Spruce wood resists decay and is not affected by the attack of marine borers. It is however liable to shrink, twist and warp. It is used for piles under water and (formerly) for aeroplane construction. Sundri | Heritiera fomes | Dark red | 960 kg/m³ | Bengal | It is hard and tough. It is difficult to season and work. It is elastic and close grained. It is strong and durable. These qualities make it suited for such uses as boat building, piles, poles, tool handles, and carriage shafts. Tamarind | Tamarindus indica | Dark brown | 1280 kg/m³[citation needed] | All over India | Tamarind is knotty and durable. It is a beautiful tree for avenue and gardens. Its development is very slow but it ultimately forms a massive appearance. Its fruit is also very useful. It is used for agricultural instruments, well curbs, sugar mills, carts and brick burning. Teak | Tectona grandis | Deep yellow to dark brown | 639 kg/m³ | Central India and Southern India | Moderately hard, teak is durable and fire-resistant. It can be easily seasoned and worked. It takes up a good polish and is not attacked by white ants and dry rot. It does not corrode iron fastenings and it shrinks little. It is among the most valuable timber trees of the world and its use is limited to superior work only. Toon, Red Cedar | Toona ciliata | Reddish brown or dull red | 450 kg/m³ | Assam | It can be easily worked. It is light in weight. It is used for such products as furniture, packing boxes, cabinet making and door panels.
WTQ_for_TSD
Common name | Binomial nomenclature | Colour | Density ¹ | Location | Characteristics, Usage and Status Aini or Aangili | Artocarpus hirsutus | Yellowish brown | 595 kg/m³ | Maharashtra, Andhra Pradesh, Tamil Nadu, Karnataka, Kerala | Elastic, close-grained, and strong. It takes polish. It can be used underwater. It is used for ordinary building construction, structural work, paving, furniture and so forth. Arjun | Terminalia arjuna Terminalia elliptica | Dark brown | 870 kg/m³ | Central India | It is heavy and strong. It has such uses as beams, rafters, and posts. Axlewood | Anogeissus latifolia | | 930 kg/m³ | Andhra Pradesh, Tamil Nadu, Maharashtra, Madhya Pradesh, Bihar, Uttar Pradesh | It is very strong, hard and tough. It takes a smooth finish. It is subject to cracking. Babul | Acacia nilotica subsp. indica | Whitish red | 835 kg/m³ | Rajasthan, Andhra Pradesh, Maharashtra, Madhya Pradesh, Tamil Nadu, Karnataka, Bengal, Gujarat, Uttar Pradesh | It is strong, hard and tough and it takes up a good polish. It is used for such products as bodies and wheels of bullock cart, agricultural instruments, tool handles, and well curbs. Bakul | Mimusops elengi Mimusops parvifolia | Reddish brown | 880 kg/m³ | Some parts of North India | It is close-grained and tough. It is used for making cabinets. Bamboo | Family Poaceae, tribe Bambuseae | | | Throughout India, especially Assam and Bengal | Not actually a tree, but a woody grass, it is flexible, very strong and durable. It is used for scaffoldings, thatched roofs, rafters, temporary bridges, and so forth. Banyan | Ficus benghalensis | Brown | 580 kg/m³ | Throughout India | It is strong and durable only under water. The aerial roots are utilized for such items as tent poles and well curbs. Benteak | Lagerstoemia parviflora | | 675 kg/m³ | Kerala, Madras, Maharashtra, Karnataka | It is strong and takes up a smooth surface. It may be used for building constructions, boat building and furniture. Bijasal | Pterocarpus marsupium | Light brown | 800 kg/m³ | Karnataka, Andhra Pradesh, Madhya Pradesh, Maharashtra, Kerala, Uttar Pradesh, Tamil Nadu, Orissa | It is coarse-grained, durable and strong but difficult to work. Termites (also known as white ant) do not easily attack it. It is used for ordinary building construction and for cart wheels. Vulnerable Casuarina | Casuarina spp. | Reddish brown | 765 kg/m³ | Andhra Pradesh, Tamil Nadu | It grows straight. It is strong and fibrous. It is, however, badly twisted. It is often used for scaffolding and posts for temporary structures. Coconut | Cocos nucifera | Reddish brown | | Throughout coastal India | Takes polish. Requires preservative treatment. Used as poles, piles, furniture and as formwork in concrete construction. Deodar | Cedrus deodara | Yellowish brown | 560 kg/m³ | Himalayas, Punjab, Uttar Pradesh | Deodar is the most important timber tree providing soft wood. It can be easily worked and it is moderately strong. It possesses distinct annual rings. It is used for making cheap furniture, railway carriages, railway sleepers, packing boxes, structural work and so forth. Gambar | Gmelina arborea | Pale yellow | 580 kg/m³ | Central India, South India | It can be easily worked and is strong and durable especially when used under water. It is used for such products as furniture, carriage, well curbs, yokes, and door panels. Hopea | Hopea parviflora | Light to deep brown | 1010 kg/m³ | Madras, Kerala | Hopea is extremely strong and tough. It is difficult to work. However, it can be seasoned easily and it is durable and not likely to be damaged by white ants. It has been variously used for ordinary house construction, railway sleepers, piles, and boat building. Endangered Himalayan Elm, Indian Elm | Ulmus wallichiana | Red | 960 kg/m³ | Throughout India | It is moderately hard and strong. It is used for door and window frames, carts, and so forth. Ironwood, Penaga Lilin, Bosneak, Gangaw, Mesua | Mesua ferrea | Reddish brown | 960–1060 kg/m³ | | Ironwood is durable though it is very hard and is not easily worked. It even resists penetration of nails. It is used for ordinary house construction, bridges, piles, agricultural instruments, railway wagons, and railway sleepers. Irul, Pyinkado | Xylia xylocarpa | | 830–1060 kg/m³ | Karnataka, Kerala, Andhra Pradesh, Maharashtra, Orissa, Tamil Nadu | It is very hard, heavy and durable. Difficult to work, it also requires slow and careful seasoning. It is used for railway sleepers, agricultural instruments, paving blocks, and heavy construction. Least concern Jack | Mangifera caesia. | Yellow, darkens with age | 595 kg/m³ | Karnataka, Maharashtra, Tamil Nadu, Kerala | It is compact and even grained. It is moderately strong and easy to work. It takes a good finish and maintains its shape well. It has many uses including plain furniture, boat construction, well curbs, door panels, cabinet making and musical instruments. Jarul | Lagerstroemia flos-reginae | Light reddish gray | 640 kg/m³ | Assam, Bengal, Maharashtra | Hard and durable, it can be easily worked. It takes a good finish and is used for house construction, boat building, railway carriages, cart making and scaffolding. Kathal, Keledang, Jackfruit | Artocarpus heterophyllus | Yellow to deep brown | 800 kg/m³ | Karnataka, Andhra Pradesh, Kerala, Maharashtra, Tamil Nadu | It is heavy and hard. It is durable under water and in damp conditions, however, it cracks if exposed to direct sun. White ants do not attack it. It is used for piles, platforms of wooden bridges, door and window panels. Lauraceae, Saj | Lauraceae | Dark brown | 880 kg/m³ | Karnataka, Andhra Pradesh, Bihar, Orissa, Madhya Pradesh, Kerala, Tamil Nadu | It is strong, hard and tough. It is subject to cracking and attack by dry rot. White ants do not attack it. It takes a smooth finish. It is used for such purposes as house construction, boat construction, railway sleepers and structural work. Mahogany | Swietenia spp. | Reddish brown | 720 kg/m³ | | It takes a good polish and is easily worked. It is durable under water. It is most commonly used for furniture, pattern making and cabinet work. Mango | Mangifera spp | Deep gray | 560–720 kg/m³ | Throughout India | The mango tree is well known for its fruits. It is easy to work and it maintains its shape well. It is moderately strong. It is most often used for cheap furniture, toys, packing boxes, cabinet work, panels for doors and for windows. Mulberry | Morus spp. | Brown | 650 kg/m³ | Punjab | It is strong, tough and elastic. It takes up a clean finish. It can be well seasoned. It is turned and carved easily. Mulberry is typically used for baskets and sports goods like hockey sticks, tennis rackets and cricket bats. Oak | Quercus spp. | Yellowish brown | 865 kg/m³ | | Oak is strong and durable, with straight silvery grain. It is used for preparing sporting goods. Palm | Arecaceae | Dark brown | 1040 kg/m³ | Throughout India | It contains ripe wood in the outer crust. The colour of this ripened wood is dark brown. It is strong, durable and fibrous. Palm is used for furniture, roof covering, rafters and joists. Pine | Pinus spp. | | | | Pine wood is hard and tough except white pine which is soft. It decays easily if it comes into contact with soil. It is heavy and coarse grained. It is used for pattern making, frames for doors and windows, and for paving material. White pine is light and straight grained and is used in the manufacture of matches. Red cedar | | Red | 480 kg/m³ | Assam, Nagpur | It is soft and even grained. It is used for furniture, door panels and well curbs. Rosewood | Dalbergia latifolia | Dark | 850 kg/m³ | Kerala, Karnataka, Maharashtra, Madhya Pradesh, Tamil Nadu, Orrissa | It is strong, tough and close-grained. It is a handsome wood that takes up a high polish. It maintains its shape well and is available in large sizes. It is used for furniture of superior quality, cabinet work, ornamental carvings and so forth. Vulnerable Sal | Shorea robusta | Brown | 880–1050 kg/m³ | Karnataka, Andhra Pradesh, Maharashtra, Uttar Pradesh, Bihar, Madhya Pradesh, Orissa | It is hard, fibrous and close-grained. It does not take up a good polish. It requires slow and careful seasoning. It is durable under ground and water. It is used for railway sleepers, shipbuilding, and bridges. Sandalwood | Santalum spp. | White or Red | 930 kg/m³ | Karnataka, Tamil Nadu, Kerala, Assam, Nagpur, Bengal | It has a pleasant smell. It is commonly used for agricultural instruments, well curbs, wheels, and mallets. Vulnerable Satinwood | Chloroxylon swietenia | Yellow | 960 kg/m³ | Central and Southern India | It is very hard and durable. It is close grained. It is used for furniture and other ornamental works. Vulnerable Simul | Bombax spp. | White | 450 kg/m³ | All over India | It is a loose grained, inferior quality wood. Light in weight, it is used for packing cases, the match industry, well curbs, and for cheap furniture. Siris | Albizia spp. | Dark brown | | North India | Hard and durable, Siris wood is difficult to work. It is used for well curbs in salty water, beams, posts, and furniture. Sissoo | Dalbergia sissoo | Dark brown | 770 kg/m³ | Mysore, Maharashtra, Assam, Bengal, Uttar Pradesh, Orissa | Also known as shisham or tali, this wood is strong and tough. It is durable and handsome and it maintains its shape well. It can be easily seasoned. It is difficult to work but it takes a fine polish. It is used for high quality furniture, plywoods, bridge piles, sport goods, railway sleepers and so forth. It is a very good material for decorative works and carvings. Spruce | Picea spp. | | 480 kg/m³ | | Spruce wood resists decay and is not affected by the attack of marine borers. It is however liable to shrink, twist and warp. It is used for piles under water and (formerly) for aeroplane construction. Sundri | Heritiera fomes | Dark red | 960 kg/m³ | Bengal | It is hard and tough. It is difficult to season and work. It is elastic and close grained. It is strong and durable. These qualities make it suited for such uses as boat building, piles, poles, tool handles, and carriage shafts. Tamarind | Tamarindus indica | Dark brown | 1280 kg/m³[citation needed] | All over India | Tamarind is knotty and durable. It is a beautiful tree for avenue and gardens. Its development is very slow but it ultimately forms a massive appearance. Its fruit is also very useful. It is used for agricultural instruments, well curbs, sugar mills, carts and brick burning. Teak | Tectona grandis | Deep yellow to dark brown | 639 kg/m³ | Central India and Southern India | Moderately hard, teak is durable and fire-resistant. It can be easily seasoned and worked. It takes up a good polish and is not attacked by white ants and dry rot. It does not corrode iron fastenings and it shrinks little. It is among the most valuable timber trees of the world and its use is limited to superior work only. Toon, Red Cedar | Toona ciliata | Reddish brown or dull red | 450 kg/m³ | Assam | It can be easily worked. It is light in weight. It is used for such products as furniture, packing boxes, cabinet making and door panels.
This is a table picture. Can you figure out the row and column numbers for this particular table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_261
WTQ_203-csv_479.jpg
Please determine the total count of rows and columns in the provided table, respectively. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> Pos | No | Driver | Constructor | Laps | Time/Retired | Grid | Points 1 | 12 | Jack Brabham | Brabham-Repco | 48 | 1:48:31.3 | 4 | 9 2 | 22 | Mike Parkes | Ferrari | 48 | + 9.5 | 3 | 6 3 | 14 | Denny Hulme | Brabham-Repco | 46 | + 2 laps | 9 | 4 4 | 6 | Jochen Rindt | Cooper-Maserati | 46 | + 2 laps | 5 | 3 5 | 26 | Dan Gurney | Eagle-Climax | 45 | + 3 laps | 14 | 2 6 | 44 | John Taylor | Brabham-BRM | 45 | + 3 laps | 15 | 1 7 | 36 | Bob Anderson | Brabham-Climax | 44 | + 4 laps | 12 | 8 | 8 | Chris Amon | Cooper-Maserati | 44 | + 4 laps | 7 | NC | 42 | Guy Ligier | Cooper-Maserati | 42 | Not Classified | 11 | Ret | 2 | Pedro Rodríguez | Lotus-Climax | 40 | Oil Leak | 13 | NC | 20 | Lorenzo Bandini | Ferrari | 37 | Not Classified | 1 | NC | 30 | Jo Bonnier | Brabham-Climax | 32 | Not Classified | 17 | Ret | 16 | Graham Hill | BRM | 13 | Engine | 8 | Ret | 38 | Jo Siffert | Cooper-Maserati | 10 | Fuel System | 6 | Ret | 32 | Mike Spence | Lotus-BRM | 8 | Clutch | 10 | Ret | 10 | John Surtees | Cooper-Maserati | 5 | Fuel System | 2 | Ret | 4 | Peter Arundell | Lotus-BRM | 3 | Gearbox | 16 | DNS | 2 | Jim Clark | Lotus-Climax | | Accident | (18) |
WTQ_for_TSD
Pos | No | Driver | Constructor | Laps | Time/Retired | Grid | Points 1 | 12 | Jack Brabham | Brabham-Repco | 48 | 1:48:31.3 | 4 | 9 2 | 22 | Mike Parkes | Ferrari | 48 | + 9.5 | 3 | 6 3 | 14 | Denny Hulme | Brabham-Repco | 46 | + 2 laps | 9 | 4 4 | 6 | Jochen Rindt | Cooper-Maserati | 46 | + 2 laps | 5 | 3 5 | 26 | Dan Gurney | Eagle-Climax | 45 | + 3 laps | 14 | 2 6 | 44 | John Taylor | Brabham-BRM | 45 | + 3 laps | 15 | 1 7 | 36 | Bob Anderson | Brabham-Climax | 44 | + 4 laps | 12 | 8 | 8 | Chris Amon | Cooper-Maserati | 44 | + 4 laps | 7 | NC | 42 | Guy Ligier | Cooper-Maserati | 42 | Not Classified | 11 | Ret | 2 | Pedro Rodríguez | Lotus-Climax | 40 | Oil Leak | 13 | NC | 20 | Lorenzo Bandini | Ferrari | 37 | Not Classified | 1 | NC | 30 | Jo Bonnier | Brabham-Climax | 32 | Not Classified | 17 | Ret | 16 | Graham Hill | BRM | 13 | Engine | 8 | Ret | 38 | Jo Siffert | Cooper-Maserati | 10 | Fuel System | 6 | Ret | 32 | Mike Spence | Lotus-BRM | 8 | Clutch | 10 | Ret | 10 | John Surtees | Cooper-Maserati | 5 | Fuel System | 2 | Ret | 4 | Peter Arundell | Lotus-BRM | 3 | Gearbox | 16 | DNS | 2 | Jim Clark | Lotus-Climax | | Accident | (18) |
Please determine the total count of rows and columns in the provided table, respectively. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_262
WTQ_203-csv_870.jpg
How many rows and columns does the given table have? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Iteration | Year | Dates | Location | Theme 1st | 1972 | 6 May-20 May | Suva, Fiji | \Preserving culture\"" 2nd | 1976 | 6 March-13 March | Rotorua, New Zealand | \Sharing culture\"" 3rd | 1980 | 30 June-12 July | Port Moresby, Papua New Guinea | \Pacific awareness\"" 4th | 1985 | 29 June-15 July | Tahiti, French Polynesia | \My Pacific\"" 5th | 1988 | 14 August-24 August | Townsville, Australia | \Cultural interchange\"" 6th | 1992 | 16 October-27 October | Rarotonga, Cook Islands | \Seafaring heritage\"" 7th | 1996 | 8 September-23 September | Apia, Sāmoa | \Unveiling treasures\"" 8th | 2000 | 23 October-3 November | Nouméa, New Caledonia | \Words of past | present | future\"" 9th | 2004 | 22 July-31 July | Koror, Palau | \Nurture | Regenerate | Celebrate\"" 10th | 2008 | 20 July-2 August | Pago Pago, American Samoa | \Threading the Oceania ‘Ula\"" 11th | 2012 | 1–14 July | Honiara, Solomon Islands | \Culture in Harmony with Nature\"" 12th | 2016 | TBA | Tumon, Guam | \TBA\"" 13th | 2020 | TBA | TBA, Hawaii | \TBA\""
WTQ_for_TSD
Iteration | Year | Dates | Location | Theme 1st | 1972 | 6 May-20 May | Suva, Fiji | \Preserving culture\"" 2nd | 1976 | 6 March-13 March | Rotorua, New Zealand | \Sharing culture\"" 3rd | 1980 | 30 June-12 July | Port Moresby, Papua New Guinea | \Pacific awareness\"" 4th | 1985 | 29 June-15 July | Tahiti, French Polynesia | \My Pacific\"" 5th | 1988 | 14 August-24 August | Townsville, Australia | \Cultural interchange\"" 6th | 1992 | 16 October-27 October | Rarotonga, Cook Islands | \Seafaring heritage\"" 7th | 1996 | 8 September-23 September | Apia, Sāmoa | \Unveiling treasures\"" 8th | 2000 | 23 October-3 November | Nouméa, New Caledonia | \Words of past | present | future\"" 9th | 2004 | 22 July-31 July | Koror, Palau | \Nurture | Regenerate | Celebrate\"" 10th | 2008 | 20 July-2 August | Pago Pago, American Samoa | \Threading the Oceania ‘Ula\"" 11th | 2012 | 1–14 July | Honiara, Solomon Islands | \Culture in Harmony with Nature\"" 12th | 2016 | TBA | Tumon, Guam | \TBA\"" 13th | 2020 | TBA | TBA, Hawaii | \TBA\""
How many rows and columns does the given table have? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_263
WTQ_203-csv_556.jpg
How many rows and columns does the given table have? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Year | Competition | Venue | Position | Notes 2005 | World Youth Championships | Marrakech, Morocco | 6th | 5.05 m 2006 | World Junior Championships | Beijing, China | 5th | 5.30 m 2008 | Olympic Games | Beijing, China | 10th | 5.45 m 2009 | European U23 Championships | Kaunas, Lithuania | 8th | 5.15 m 2009 | World Championships | Berlin, Germany | 22nd (q) | 5.40 m 2010 | European Championships | Barcelona, Spain | 10th | 5.60 m 2011 | World Championships | Daegu, South Korea | 9th | 5.65 m 2012 | European Championships | Helsinki, Finland | 6th | 5.60 m 2012 | Olympic Games | London, United Kingdom | 8th | 5.65 m 2013 | European Indoor Championships | Gothenburg, Sweden | 5th | 5.71 m 2014 | World Indoor Championships | Sopot, Poland | 3rd | 5.80 m
WTQ_for_TSD
Year | Competition | Venue | Position | Notes 2005 | World Youth Championships | Marrakech, Morocco | 6th | 5.05 m 2006 | World Junior Championships | Beijing, China | 5th | 5.30 m 2008 | Olympic Games | Beijing, China | 10th | 5.45 m 2009 | European U23 Championships | Kaunas, Lithuania | 8th | 5.15 m 2009 | World Championships | Berlin, Germany | 22nd (q) | 5.40 m 2010 | European Championships | Barcelona, Spain | 10th | 5.60 m 2011 | World Championships | Daegu, South Korea | 9th | 5.65 m 2012 | European Championships | Helsinki, Finland | 6th | 5.60 m 2012 | Olympic Games | London, United Kingdom | 8th | 5.65 m 2013 | European Indoor Championships | Gothenburg, Sweden | 5th | 5.71 m 2014 | World Indoor Championships | Sopot, Poland | 3rd | 5.80 m
How many rows and columns does the given table have? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_264
WTQ_204-csv_825.jpg
What is the count of rows and columns in the given table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Year | Winner | Jockey | Trainer | Owner | Distance (Miles) | Time | Win $ 2013 | Alterlite (FR) | John R. Velazquez | Chad C. Brown | Martin S. Schwartz | 1-1/8 | 1:50.55 | $500,000 2012 | Samitar | Ramon Dominguez | Chad C. Brown | Martin S. Schwartz | 1-1/8 | 1:48.74 | $180,000 2011 | Winter Memories | Javier Castellano | James J. Toner | Phillips Racing Partnership | 1-1/8 | 1:51.06 | $150,000 2010 | Check the Label | Ramon Dominguez | H. Graham Motion | Lael Stables | 1-1/8 | 1:51.41 | $150,000 2009 | Miss World | Cornelio Velasquez | Christophe Clement | Waratah Thoroughbreds | 1-1/8 | 1:53.55 | $180,000 2008 | Backseat Rhythm | Javier Castellano | Patrick L. Reynolds | Paul P. Pompa Jr. | 1-1/8 | 1:51.82 | $150,000 2007 | Alexander Tango | Shaun Bridgmohan | Tommy Stack | Noel O' Callaghan | 1-1/8 | 1:48.97 | $120,000 2006 | Magnificent Song | Garrett Gomez | Todd A. Pletcher | Parrish,Malcolm,Edward | 1-1/8 | 1:48.48 | $150,000 2005 | Luas Line | John Velazquez | David Wachman | Evelyn M. Stockwell | 1-1/8 | 1:45.62 | $180,000 2004 | Lucifer's Stone | Jose A. Santos | Linda L. Rice | Team Solaris Stable | 1-1/8 | 1:48.88 | $180,000 2003 | Indy Five Hundred | Pat Day | Robert Barbara | Georgica Stable | 1-1/8 | 1:48.44 | $150,000 2002 | Wonder Again | Edgar Prado | James J. Toner | Joan G. & John W. Phillips | 1-1/8 | 1:47.33 | $150,000 2001 | Voodoo Dancer | Corey Nakatani | Christophe Clement | Green Hills Farms | 1-1/8 | 1:47.69 | $150,000 2000 | Gaviola | Jerry D. Bailey | William H. Turner, Jr. | Twilite Farms | 1-1/8 | 1:48.89 | $150,000 1999 | Perfect Sting | Pat Day | Joseph Orseno | Stronach Stable | 1-1/8 | 1:49.41 | $129,900 1998 | Pharatta-IR | Corey Nakatani | Carlos Laffon-Parias | Hinojosa Dario | 1-1/8 | 1:47.10 | $129,720 1997 | Auntie Mame | Jerry D. Bailey | Angel Penna, Jr. | Lazy F Ranch | 1-1/8 | 1:48.49 | $128,040 1996 | True Flare | Gary L. Stevens | Robert J. Frankel | Juddmonte Farms | 1-1/16 | 1:42.58 | $128,460 1995 | Perfect Arc | John Velazquez | Angel Penna, Jr. | Brazil Stables | 1-1/16 | 1:42.35 | $101,070 1994 | Jade Flush | Robbie Davis | Nicholas P. Zito | Condren, et al. | 1-1/16 | 1:46.79 | $67,140 1993 | Sky Beauty | Mike E. Smith | H. Allen Jerkens | Georgia E. Hofmann | 1 | 1:35.76 | $68,400 1992 | November Snow | Chris Antley | H. Allen Jerkens | Earle I. Mack | 1 | 1:35.91 | $66,480 1991 | Dazzle Me Jolie | Jose A. Santos | Willard J. Thompson | Jolie Stanzione | 1 | 1:35.61 | $72,000 1990 | Aishah | Jose A. Santos | Flint S. Schulhofer | Helen K. Groves | 1 | 1:35.40 | $57,690 1989 | Highest Glory | Jose A. Santos | D. Wayne Lukas | H. Joseph Allen | 1 | 1:37.20 | $70,440 1988 | Topicount | Angel Cordero, Jr. | H. Allen Jerkens | Centennial Farms | 1 | 1:38.00 | $82,260 1987 | Personal Ensign | Randy Romero | Claude R. McGaughey III | Ogden Phipps | 1 | 1:36.60 | $82,140 1986 | Life At The Top | Chris McCarron | D. Wayne Lukas | Lloyd R. French | 1 | 1:34.40 | $51,210 1985 | Kamikaze Rick | Angel Cordero, Jr. | John Parisella | Theodore M. Sabarese | 1 | 1:36.00 | $50,490 1984 | Given | Matthew Vigliotti | Alfino Pepino | Ronald S. Green | 1-1/16 | 1:43.40 | $42,960 1983 | Pretty Sensible | Alfredo Smith, Jr. | George Travers | John Zervas | 1 | 1:37.80 | $33,600 1982 | Nafees | Jorge Velasquez | Richard T. DeStasio | Albert Fried, Jr. | 1 | 1:38.40 | $33,120 1981 | Banner Gala | Angel Cordero, Jr. | Angel Penna, Sr. | Ogden Phipps | 1 | 1:35.60 | $33,900 1980 | Mitey Lively | Jorge Velasquez | Douglas R. Peterson | Tayhill Stable | 1 | 1:36.40 | $33,480 1979 | Danielle B. | Ruben Hernandez | John O. Hertler | Our Precious Stable | 1-1/16 | 1:45.40 | $33,000 1978 | Late Bloomer | Jorge Velasquez | John M. Gaver, Jr. | Greentree Stable | 1-1/16 | 1:41.60 |
WTQ_for_TSD
Year | Winner | Jockey | Trainer | Owner | Distance (Miles) | Time | Win $ 2013 | Alterlite (FR) | John R. Velazquez | Chad C. Brown | Martin S. Schwartz | 1-1/8 | 1:50.55 | $500,000 2012 | Samitar | Ramon Dominguez | Chad C. Brown | Martin S. Schwartz | 1-1/8 | 1:48.74 | $180,000 2011 | Winter Memories | Javier Castellano | James J. Toner | Phillips Racing Partnership | 1-1/8 | 1:51.06 | $150,000 2010 | Check the Label | Ramon Dominguez | H. Graham Motion | Lael Stables | 1-1/8 | 1:51.41 | $150,000 2009 | Miss World | Cornelio Velasquez | Christophe Clement | Waratah Thoroughbreds | 1-1/8 | 1:53.55 | $180,000 2008 | Backseat Rhythm | Javier Castellano | Patrick L. Reynolds | Paul P. Pompa Jr. | 1-1/8 | 1:51.82 | $150,000 2007 | Alexander Tango | Shaun Bridgmohan | Tommy Stack | Noel O' Callaghan | 1-1/8 | 1:48.97 | $120,000 2006 | Magnificent Song | Garrett Gomez | Todd A. Pletcher | Parrish,Malcolm,Edward | 1-1/8 | 1:48.48 | $150,000 2005 | Luas Line | John Velazquez | David Wachman | Evelyn M. Stockwell | 1-1/8 | 1:45.62 | $180,000 2004 | Lucifer's Stone | Jose A. Santos | Linda L. Rice | Team Solaris Stable | 1-1/8 | 1:48.88 | $180,000 2003 | Indy Five Hundred | Pat Day | Robert Barbara | Georgica Stable | 1-1/8 | 1:48.44 | $150,000 2002 | Wonder Again | Edgar Prado | James J. Toner | Joan G. & John W. Phillips | 1-1/8 | 1:47.33 | $150,000 2001 | Voodoo Dancer | Corey Nakatani | Christophe Clement | Green Hills Farms | 1-1/8 | 1:47.69 | $150,000 2000 | Gaviola | Jerry D. Bailey | William H. Turner, Jr. | Twilite Farms | 1-1/8 | 1:48.89 | $150,000 1999 | Perfect Sting | Pat Day | Joseph Orseno | Stronach Stable | 1-1/8 | 1:49.41 | $129,900 1998 | Pharatta-IR | Corey Nakatani | Carlos Laffon-Parias | Hinojosa Dario | 1-1/8 | 1:47.10 | $129,720 1997 | Auntie Mame | Jerry D. Bailey | Angel Penna, Jr. | Lazy F Ranch | 1-1/8 | 1:48.49 | $128,040 1996 | True Flare | Gary L. Stevens | Robert J. Frankel | Juddmonte Farms | 1-1/16 | 1:42.58 | $128,460 1995 | Perfect Arc | John Velazquez | Angel Penna, Jr. | Brazil Stables | 1-1/16 | 1:42.35 | $101,070 1994 | Jade Flush | Robbie Davis | Nicholas P. Zito | Condren, et al. | 1-1/16 | 1:46.79 | $67,140 1993 | Sky Beauty | Mike E. Smith | H. Allen Jerkens | Georgia E. Hofmann | 1 | 1:35.76 | $68,400 1992 | November Snow | Chris Antley | H. Allen Jerkens | Earle I. Mack | 1 | 1:35.91 | $66,480 1991 | Dazzle Me Jolie | Jose A. Santos | Willard J. Thompson | Jolie Stanzione | 1 | 1:35.61 | $72,000 1990 | Aishah | Jose A. Santos | Flint S. Schulhofer | Helen K. Groves | 1 | 1:35.40 | $57,690 1989 | Highest Glory | Jose A. Santos | D. Wayne Lukas | H. Joseph Allen | 1 | 1:37.20 | $70,440 1988 | Topicount | Angel Cordero, Jr. | H. Allen Jerkens | Centennial Farms | 1 | 1:38.00 | $82,260 1987 | Personal Ensign | Randy Romero | Claude R. McGaughey III | Ogden Phipps | 1 | 1:36.60 | $82,140 1986 | Life At The Top | Chris McCarron | D. Wayne Lukas | Lloyd R. French | 1 | 1:34.40 | $51,210 1985 | Kamikaze Rick | Angel Cordero, Jr. | John Parisella | Theodore M. Sabarese | 1 | 1:36.00 | $50,490 1984 | Given | Matthew Vigliotti | Alfino Pepino | Ronald S. Green | 1-1/16 | 1:43.40 | $42,960 1983 | Pretty Sensible | Alfredo Smith, Jr. | George Travers | John Zervas | 1 | 1:37.80 | $33,600 1982 | Nafees | Jorge Velasquez | Richard T. DeStasio | Albert Fried, Jr. | 1 | 1:38.40 | $33,120 1981 | Banner Gala | Angel Cordero, Jr. | Angel Penna, Sr. | Ogden Phipps | 1 | 1:35.60 | $33,900 1980 | Mitey Lively | Jorge Velasquez | Douglas R. Peterson | Tayhill Stable | 1 | 1:36.40 | $33,480 1979 | Danielle B. | Ruben Hernandez | John O. Hertler | Our Precious Stable | 1-1/16 | 1:45.40 | $33,000 1978 | Late Bloomer | Jorge Velasquez | John M. Gaver, Jr. | Greentree Stable | 1-1/16 | 1:41.60 |
What is the count of rows and columns in the given table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_265
WTQ_203-csv_32.jpg
Please identify the row and column numbers of the table displayed in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Character | Real name | Home world | Membership notes | Powers Night Girl | Lydda Jath | Kathoon | Pre-Crisis version first appeared in Adventure Comics #306 (March 1963). Legion membership first mentioned by Starman in Justice Society of America vol. 3, #6 (July 2007) and confirmed in Action Comics #860 (February 2008). | Super-strength when not in direct sunlight. Chameleon Girl | Yera Allon | Durla | Pre-Crisis version first appeared (impersonating Shrinking Violet) in Legion of Super-Heroes vol. 2, #286 (April 1982). True form and identity revealed in Legion of Super-Heroes vol. 2, #305 (November 1983). Legion membership first revealed in Action Comics #861 (March 2008). | Shapeshifting. Karate Kid II | Myg | Lythyl | Joined as a replacement for Val Armorr, as revealed in Final Crisis: Legion of 3 Worlds #1 (October 2008), unlike his counterpart who did not join the original team prior to Crisis on Infinite Earths. Killed by Radiation Roy in Final Crisis: Legion of 3 Worlds #3 (April 2009). | Mastery of all known martial arts. Green Lantern | Rond Vidar | Earth | Pre-Crisis version first appeared in Adventure Comics #349 (October 1966); granted honorary membership in Adventure Comics #360 (September 1967). Last remaining member of the Green Lantern Corps, as revealed in Final Crisis: Legion of 3 Worlds #2 (November 2008). Killed in the same issue by Superboy-Prime. | Possesses a Green Lantern power ring. XS | Jenni Ognats | Aarok | First appeared in Legionnaires #0 (October 1994); granddaughter of Barry Allen and first cousin of Bart Allen. Native of the same universe as the post-Infinite Crisis team, as revealed in Final Crisis: Legion of 3 Worlds #3 (April 2009). Joined the Earth-247 team in Legion of Super-Heroes vol. 4, #62 (November 1994). Joined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009). Post-Flashpoint no longer listed as a member of the Legion. | Superspeed. Gates | Ti'julk Mr'asz | Vyrga | First appeared in Legion of Super-Heroes vol. 4, #66 (March 1995). Joined the Earth-247 team in Legion of Super-Heroes vol. 4, #76 (January 1996). Joined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009). | Creation of teleportation \gates\"." Earth-Man | Kirt Niedrigh | Earth | Pre-Crisis version first appeared (as \Absorbency Boy\") in Superboy and the Legion of Super-Heroes #218 (July 1976). Joined in Legion of Super-Heroes vol. 6 | #2 (August 2010). Died battling the Adversary in Legion of Super-Heroes vol. 6 | #16 (October 2011)." | Super-power absorption and duplication. Comet Queen | Grava | Extal Colony | Pre-Crisis version first appeared in Legion of Super-Heroes vol. 2, #304 (October 1983) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Space flight, comet gas extrusion. Chemical Kid | Hadru Jamik | Phlon | First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Catalyze chemical reactions. Glorith II | Glorith | Unknown | First appeared in Adventure Comics #523 (April 2011) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Manipulation of mystical energies. Dragonwing | Marya Pai | Earth | First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Fire breath and acid absorption. Harmonia | Harmonia Li | Earth | First appeared in Legion of Super-Heroes vol. 6, #1 (July 2010). Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Elemental.
WTQ_for_TSD
Character | Real name | Home world | Membership notes | Powers Night Girl | Lydda Jath | Kathoon | Pre-Crisis version first appeared in Adventure Comics #306 (March 1963). Legion membership first mentioned by Starman in Justice Society of America vol. 3, #6 (July 2007) and confirmed in Action Comics #860 (February 2008). | Super-strength when not in direct sunlight. Chameleon Girl | Yera Allon | Durla | Pre-Crisis version first appeared (impersonating Shrinking Violet) in Legion of Super-Heroes vol. 2, #286 (April 1982). True form and identity revealed in Legion of Super-Heroes vol. 2, #305 (November 1983). Legion membership first revealed in Action Comics #861 (March 2008). | Shapeshifting. Karate Kid II | Myg | Lythyl | Joined as a replacement for Val Armorr, as revealed in Final Crisis: Legion of 3 Worlds #1 (October 2008), unlike his counterpart who did not join the original team prior to Crisis on Infinite Earths. Killed by Radiation Roy in Final Crisis: Legion of 3 Worlds #3 (April 2009). | Mastery of all known martial arts. Green Lantern | Rond Vidar | Earth | Pre-Crisis version first appeared in Adventure Comics #349 (October 1966); granted honorary membership in Adventure Comics #360 (September 1967). Last remaining member of the Green Lantern Corps, as revealed in Final Crisis: Legion of 3 Worlds #2 (November 2008). Killed in the same issue by Superboy-Prime. | Possesses a Green Lantern power ring. XS | Jenni Ognats | Aarok | First appeared in Legionnaires #0 (October 1994); granddaughter of Barry Allen and first cousin of Bart Allen. Native of the same universe as the post-Infinite Crisis team, as revealed in Final Crisis: Legion of 3 Worlds #3 (April 2009). Joined the Earth-247 team in Legion of Super-Heroes vol. 4, #62 (November 1994). Joined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009). Post-Flashpoint no longer listed as a member of the Legion. | Superspeed. Gates | Ti'julk Mr'asz | Vyrga | First appeared in Legion of Super-Heroes vol. 4, #66 (March 1995). Joined the Earth-247 team in Legion of Super-Heroes vol. 4, #76 (January 1996). Joined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009). | Creation of teleportation \gates\"." Earth-Man | Kirt Niedrigh | Earth | Pre-Crisis version first appeared (as \Absorbency Boy\") in Superboy and the Legion of Super-Heroes #218 (July 1976). Joined in Legion of Super-Heroes vol. 6 | #2 (August 2010). Died battling the Adversary in Legion of Super-Heroes vol. 6 | #16 (October 2011)." | Super-power absorption and duplication. Comet Queen | Grava | Extal Colony | Pre-Crisis version first appeared in Legion of Super-Heroes vol. 2, #304 (October 1983) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Space flight, comet gas extrusion. Chemical Kid | Hadru Jamik | Phlon | First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Catalyze chemical reactions. Glorith II | Glorith | Unknown | First appeared in Adventure Comics #523 (April 2011) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Manipulation of mystical energies. Dragonwing | Marya Pai | Earth | First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy. Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Fire breath and acid absorption. Harmonia | Harmonia Li | Earth | First appeared in Legion of Super-Heroes vol. 6, #1 (July 2010). Joined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011). | Elemental.
Please identify the row and column numbers of the table displayed in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_266
WTQ_204-csv_50.jpg
Provide me with the row number and column number for the table shown in this image. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> Route | Name | Fare Type | Terminals | Terminals | Major streets | Notes | History 31 | Wisconsin Avenue Line | Local | Friendship Heights station | Potomac Park (Virginia Av & 21st St NW) | Wisconsin Avenue NW | | 31 replaces the Wisconsin Avenue portion of the old 30 (see Pennsylvania Avenue Line) 32, 36 | Pennsylvania Avenue Line | Local | Friendship Heights station | 32 Southern Avenue station 36 Naylor Road station | Wisconsin Avenue NW Pennsylvania Avenue SE/NW Branch Avenue SE (36) Alabama Avenue SE (32) | Some weekday 32 and 36 trips terminate at: Farragut Square Foggy Bottom – GWU station | 36 replaces a portion of the old 35 (see Pennsylvania Avenue Line) 34 | Naylor Rd Line | Local | Archives (10th St & Pennsylvania Av NW) | Naylor Road station | Pennsylvania Avenue SE Independence Avenue SE/SW Naylor Road SE | | 34 operated to Friendship Heights station until replaced by the M5, which operated from Naylor Road station to Eastern Market station in 2007; 34 replaced the M5 in 2008 with the extension to the Archives station, also see Pennsylvania Avenue Line 37 | Wisconsin Avenue Metro Extra Line | Limited Stop | Friendship Heights station | Archives station (AM End) Federal Triangle (10th St & Pennsylvania Av NW) (PM Start) | Wisconsin Avenue NW Massachusetts Avenue NW Pennsylvania Avenue NW | Weekday peak hour service only (AM to Archives, PM to Friendship Heights) Limited Stops Only | A prior \incarnation\" of the 37 was once known as the Wisconsin Avenue Express Line | running from Tenleytown-AU station to Archives until the early 1990s" 39 | Pennsylvania Avenue Metro Extra Line | Limited Stop | Naylor Road station | Potomac Park (Virginia Av & 21st St NW) | Pennsylvania Avenue SE/NW | Weekday peak hour service only AM to Potomac Park, PM to Naylor Road Limited Stops Only | 42, 43 | Mount Pleasant Line | Local | Mount Pleasant (Mount Pleasant & Lamont Streets NW) | 42 Gallery Place station 43 Farragut Square (AM End) 43 McPherson Square station (Franklin Square Entrance) (PM Start) | 42 Mount Pleasant Street NW, Columbia Road NW, Connecticut Avenue NW, H/I Streets NW 43 Mount Pleasant Street NW, Columbia Road NW, Connecticut Avenue NW | 42 serves Dupont Circle station some peak hour trips terminate at Farragut Square 43: weekday peak hour service only Travels underneath Dupont Circle via the Connecticut Avenue underpass) | See Mount Pleasant Line 52, 53, 54 | 14th Street Line | Local | Takoma station 14th Street & Colorado Ave NW | 52, 54 L'Enfant Plaza Metrorail Station (7th & D Streets SW) 53 McPherson Square station (Franklin Square Entrance) | 14th Street NW Pennsylvania Avenue NW (54) Independence Avenue SW (52) | 52 and 54: daily 53: Monday-Saturday only | 52 & 54 originally terminated at Navy Yard until the mid-1990s, when the 52 was truncated to L'Enfant Plaza station & 54 to Federal Triangle. 54 was later extended to L'Enfant Plaza station. The 53 was introduced several years after the former route 50 was discontinued, operating at first to Bureau Of Engraving before being shortened to Federal Triangle and now to Franklin Square. Also see 14th Street Line 62, 63 | Takoma-Petworth Line | Local | Takoma station | 62 Georgia Avenue – Petworth station 63 Federal Triangle (10th St & Constitution Av NW) | 5th Street NW, Kansas Avenue NW, Sherman Avenue NW (63) 13th Street NW (63) | 63: weekday peak & early weekend AM hours only | 63 operates through the portion of the 62 that operated to Federal Triangle until Georgia Avenue – Petworth station opened in 1999; it also replaces the 68, which operated from Georgia Avenue – Petworth station to Federal Triangle from 2001–2009 60, 64 | Fort Totten-Petworth Line | Local | Fort Totten station | 60 Georgia Avenue – Petworth station 64 Federal Triangle (10th St & Constitution Av NW) | Rock Creek Church Rd NW (60) Upshur Street NW (60) New Hampshire Avenue NW (64) 11th Street NW (64) | 60: Monday-Friday service only | 64 was replaced by the 66 south of Georgia Avenue – Petworth station when it opened in 1999; it replaced the 66 in 2009 64 also runs on the old 11th Street Streetcar Line. 70 | Georgia Avenue-7th Street Line | Local | Silver Spring station* | Archives station | Georgia Avenue NW 7th Street NW | Silver Spring terminus is located on Wayne Avenue until completion of the Paul S. Sarbanes Transit Center. | See Seventh Street Line Starting September 23, 2011, 71 service was discontinued, and the 70 was shortened to Archives. For service to Southwest Waterfront, see route directly below this one. 74 | Convention Center-Southwest Waterfront Line | Local | Mount Vernon Square (K & 6th Streets NW) | Half & O Streets SW, or Buzzard Point (2nd & V Streets SW) | 7th Street NW/SW | Serves Buzzard Point during rush hour only | Introduced September 24, 2011 as a replacement of DC Circulator's discontinued Convention Center-Southwest Waterfront route, and to also serve the southern portion of the 70 and 71 routes. 79 | Georgia Avenue Metro Extra Line | Limited Stop | Silver Spring station* | Archives station | Georgia Avenue NW, 7th Street NW (to Silver Spring), 9th Street NW (to Archives) | limited-stop service Silver Spring terminus is located on Wayne Avenue until completion of the Paul S. Sarbanes Transit Center | 79 is a \reincarnation\" of the old 73 (Brightwood Express Line) that was discontinued roughly a decade before the 79's introduction in 2006. Saturday service began on March 24 | 2013. Sunday service began on December 29 | 2013." 80 | North Capitol Street Line | Local | Fort Totten station | Kennedy Center | 12th Street NE Michigan Avenue NE North Capitol Street H Street NW K Street NW | some peak hour and early AM/late night trips terminate at McPherson Square station | 80 operates on the old North Capitol Street Streetcar Line, which operated from Washington Circle to Brookland until 1958 It operated to Potomac Park until it replaced the portion of the old Route 81 south of Pennsylvania Avenue NW to Kennedy Center after it was discontinued in the mid-1990s 90, 92, 93 | U Street-Garfield Line | Local* | Duke Ellington Bridge or Frank D. Reeves Center (14th & U Streets NW) | 90 Anacostia station 92 Congress Heights station 93 Congress Heights station | Calvert Street NW U Street NW, Florida Avenue NW/NE 8th Street NE Good Hope Road SE (92) Stanton Road SE (93) | 93: operates when Metrorail is not open, replacing the 90 & 94 Fare: $1 (90 only, south of the 11th Street Bridge, unless transferring to another bus) | 90 replaced all portions of the 94 north of Anacostia station which became the 94's northern terminal after it opened in 1991; 90, 92, and 93 served McLean Gardens from the mid-1990s to the mid-2000s until replaced by the 96. Also see U Street Line, New Jersey Avenue Line and Florida Avenue Line 94 | Stanton Road Line | Local* | Stanton Road (19th & Savannah Streets SE) | Anacostia station | Stanton Road SE | replaced by 93 (U Street-Garfield Line) when not in operation Fare: $1 (unless transferring to another bus) | 94 used to operate to Duke Ellington Bridge (as part of the U Street-Garfield Line) until Anacostia station opened in 1991; replaced by the 90 north of Anacostia since then. 96, 97 | East Capitol Street-Cardozo Line | Local | Capitol Heights station | 96 Tenleytown-AU station 97 Union Station | East Capitol Street New Jersey Avenue NW (96) U Street NW (96) 29th Street NW (96) | 96 operates between Stadium-Armory and Tenleytown-AU stations when the 97 operates during the weekday peak hours only 97 skips DC General Health Campus. | Formerly known as the New Jersey Avenue Line 96 & 97 replaced the old Routes 40 & 44 east of Union Station in the mid-1990s. 96 extended from Duke Ellington Bridge to McLean Gardens in the mid-2000s, replacing the northwestern portion of the 90, 92, and 93. 96 was extended to Tenleytown-AU station December 30, 2012. A2, A6, A7, A8, A42, A46, A48 | Anacostia-Congress Heights Line | Local* | Southern Avenue station (A2, A42) Livingston Rd & 3rd Street SE (A6, A8, A46, A48) Southern Avenue & South Capitol Street, SE (A7) | Anacostia Station (A2, A6, A7, A8) Archives station (10th St & Pennsylvania Av NW) (A42, A46, A48) | Martin Luther King Avenue SE, Mississippi Av SE (A2, A42) Wheeler Road SE (A6, A7, A46) South Capitol Street (A8, A48) | A7: weekday peak hour service only (AM to Anacostia, PM to Livingston Road) A42, A46 and A48 operate when Metrorail is closed, replacing A2, A6, A8 (respectively) and P2*Fare: $1 (unless transferring to another bus; A42, A46, A48: south of 11th Street Bridge) | Formerly known as the Anacostia Line (along with A4 & A5) until 1991 A7 operated to L'Enfant Plaza station until Anacostia opened in 1991 A42, A46 and A48 replaced the old portions of the A2, A6 and A8 north of Anacostia station to Archives when Anacostia opened A4, W5 | Anacostia-Fort Drum Line | Local* | D.C. Village (North Parking Lot) | Anacostia station St. Elizabeth's Gate 4 (Coast Guard HQ) | Martin Luther King Avenue SE South Capitol Street | W5: weekday peak hour service only (AM to DC Village, PM to Anacostia via the Blue Plains Facility) Fare: $1 (unless transferring to another bus) A4, W5 runs to St. Elizabeth's Gate 4 (Coast Guard HQ) to D.C. Village (North Parking Lot)Weekdays Only. | A4 and A5 operated to Archives station (as part of the Anacostia Line) until Anacostia opened in 1991 The route north of Anacostia is now served by P6 The A5 covered the A4 route but excluded Fort Drum. It was discontinued on March 24, 2013, replaced by the W5 which runs on South Capitol Street (SB) and DC-295 (NB). A9 | Martin Luther King Jr Ave MetroExtra Line | Limited Stop | Livingston Road & 3rd Street, SE | McPherson Square station (Franklin Square Entrance) | Martin Luther King Jr Ave | A9: weekday MetroExtra Peak Hour service only (AM to McPherson Square, PM to Livingston Road) Limited Stops Only | A9 is now a MetroExtra Bus service as of March 24, 2013. B2 | Bladensburg Road-Anacostia Line | Local* | Mount Rainier Terminal (Rhode Island Ave & 34th Street) | Anacostia station | Bladensburg Road NE 14th Street NE (to Anacostia) 15th Street NE (to Mount Rainier) Minnesota Avenue SE | Some trips terminate at Bladensburg Road & V Street NE some PM peak hour trips start at Potomac Avenue station on school days only Fare: $1 (south of the 11th Street Bridge unless transferring to another bus) | B2 used to operate to 16th & W Streets, SE in Anacostia until Anacostia station opened in 1991 B2 then covered the portion of the old B4 & B5 routes to Barry Farms after the station opened B8, B9 | Fort Lincoln Shuttle Line | Local | B8 Fort Lincoln (Petersburg Apartments) B9 Colmar Manor (40th Place & Bladensburg Road) | Rhode Island Avenue – Brentwood station | Bladensburg Road (B9) Franklin Street NE Rhode Island Avenue NE | B8: Monday-Friday service only, except middays B9: Monday-Friday midday service only | D1 | Glover Park-Federal Triangle Line | Local | Glover Park (41st St & Davis Pl NW) | Federal Triangle (10th St & Constitution Av NW) | Q Street NW K Street NW 13th Street NW | weekday peak hour service only (AM to Federal Triangle, PM to Glover Park) | D1 operated to Union Station/Ivy City until redirected to Federal Triangle in 2010 D2 | Glover Park-Dupont Circle Line | Local | Glover Park (41st St & Davis Pl NW) | Dupont Circle station (20th & Q Sts NW Entrance) | Q Street NW | | D2 operated to Stadium-Armory station (as part of the Glover Park-Trinidad Line) until replaced by the D6 east of Dupont Circle in the mid-1990s D3 | Ivy City-Dupont Circle Line | Local | Ivy City (New York Avenue & Fenwick Street NE) | Georgetown (35th Street & Reservoir Road NW) (AM End) Dupont Circle (20th St & Massachusetts Av NW) (PM Start) | Q Street NW (to Reservoir Road) K Street NW/NE E Street NW | D3 operates weekday peak hours only (AM to Reservoir Road, PM to Ivy City) | D3 operated between Sibley Hospital and Union Station (with select peak hour service from Ivy City) until 2010 when the D1 was rerouted to Federal Triangle D4 | Ivy City-Franklin Square Line | Local | Ivy City (New York Avenue & Fenwick Street NE) | McPherson Square station (Franklin Square Entrance) | K Street NW/NE | | D4 at first operated to Sibley Hospital (as part of the Glover Park-Trinidad Line) until replaced by D6 in the mid-1990s It then operated to Union Station (as the Ivy City-Union Station Line) until 2010, when it was extended to Franklin Square D5 | MacArthur Boulevard-Georgetown Line | Local | Little Flower Church (Bethesda, MD) | Farragut Square | MacArthur Boulevard NW M Street NW Pennsylvania Avenue NW | Operates weekday peak hours only (AM to Farragut Square, PM to Little Flower Church). | Formerly known as the MacArthur Boulevard-M Street Line (with the former D9, which was discontinued in the mid-1990s) D6 | Sibley Hospital-Stadium Armory Line | Local | Sibley Hospital | Stadium-Armory station (North Entrance) | MacArthur Boulevard NW Q Street NW K Street NW E Street NW C Street NE (to Stadium-Armory) D Street NE (to Sibley Hospital) | | D6 originally operated between Glover Park & Washington Hospital Center (as part of the Glover Park-Trinidad Line) until the mid-1990s, when it was rerouted to serve Sibley Hospital (replacing the truncated D4 & D8 west of Union Station and Stadium-Armory (replacing the truncated 42 & D2 east of Dupont Circle. D8 | Hospital Center Line | Local | Washington Hospital Center | Union Station | Franklin Street NE Brentwood Road NE Mount Olivet Rd NE K Street NE | Some trips end at Rhode Island Avenue – Brentwood station during the PM peak hour period | D8 operated to Sibley Hospital (as part of the Glover Park-Trinidad Line) until replaced by the D6 (west of Union Station) in the mid-1990s E2, E3, E4 | Military Road-Crosstown Line | Local | Friendship Heights station | E2 Fort Totten station E2, E3 Ivy City (New York Av & Fenwick St NE) E4 Riggs Park (Eastern Av & Jamaica St NE) | Military Road Kennedy Street South Dakota Avenue (E2, E3) 18th Street NE (E2, E3) | E2 terminates at Fort Totten station when E3 is in operation (weekends only) E3 also serves Riggs Park (it is a combination of the E2 and E4) | E6 | Chevy Chase Line | Local | Knollwood (Knollwood Retirement Home) | Friendship Heights station | Western Avenue McKinley Street NW | | G2 | P Street-LeDroit Park Line | Local | Georgetown University (37th & O Streets NW) | LeDroit Park (Bryant & 4th Streets NW) | P Street NW | | G8 | Rhode Island Avenue Line | Local | Avondale (Eastern & Michigan Avs NE) | Farragut Square | Monroe Street NE Rhode Island Avenue NW/NE 9th Street NW (to Farragut Square) 11th Street NW (to Avondale) H Street NW | Some trips operate from Brookland-CUA station to Avondale during weekday PM peak hours | G8 is a combination of the old G4 & G6 that operated to Lafayette Square (G4) & Gallery Place station (G6) until the mid-1990s H1 | Brookland-Potomac Park Line | Local | Brookland-CUA station | Potomac Park (17th & C Streets NW) | Michigan Avenue NW/NE Columbia Road NW 23rd Street NW | weekday peak hour service only (AM to Potomac Park, PM to Brookland) | H1 was discontinued in the mid-1990s until it was \reincarnated\" in 2006" H2, H3, H4 | Crosstown Line | Local | Tenleytown-AU station | Brookland-CUA station | Wisconsin Avenue Porter Street NW Van Ness/Veazey Street NW (H2) Connecticut Avenue (H2) Columbia Road NW/Irving Street NW Michigan Avenue NW/NE | H3: weekday peak hour service only H3: Skips Washington Hospital Center | H2 & H4 operated to Fort Lincoln (east of Brookland station) until replaced by H6 in the late 1990s. They also operated to Westmoreland Circle & Western Avenue NW (west of Tenleytown station) until replaced by the N8 in the late 1990s. H3's route west of Porter Street & Connecticut Avenue NW was served by H2 until it was rerouted to serve and terminate at Van Ness Station in the early 2000s. H2 was later rerouted back to its Tenleytown terminus, replacing the N8 route east of Tenleytown and rerouting the H3 to serve exactly the same route as the H4 with the exception of Washington Hospital Center. H6 | Brookland-Fort Lincoln Line | Local | Fort Lincoln (Petersburg Apartments) | Brookland-CUA station | Franklin Street NE 14th Street NE | | H6 covers the route covered by the H2 & H4 between Brookland station & Fort Lincoln until the late 1990s H8, H9 | Park Road-Brookland Line | Local | H8 Mount Pleasant (Mount Pleasant & 17th Streets NW) H9 Archbishop Carroll High School | Rhode Island Avenue – Brentwood station | Irving Street NW (H8) Rock Creek Church Road NW (H8) 10th Street NE 12th Street NE | H9 only operates when Carroll High School is open Some H8 trips operate from Rock Creek Church Rd & Upshur Street NW to Columbia Heights station during the PM peak hours when public schools are open | K2 | Takoma-Fort Totten Line | Local | Takoma station | Fort Totten station | North Capitol Street Kansas Avenue NE Eastern Avenue | Weekday peak hour service only | K2 operated to Walter Reed Army Medical Center until 2005, when it was replaced by K1 north of Takoma station. L1, L2 | Connecticut Avenue Line | Local | Chevy Chase Circle | L1 Potomac Park (17th & C Streets NW) L2 McPherson Square station | Connecticut Avenue NW Calvert Street NW (L2) 18th Street NW (L2) 23rd Street NW (L1) K Street NW (L2) | L1 weekday peak hour service only (AM to Potomac Park, PM to Chevy Chase Circle) | M4 | Nebraska Avenue Line | Local | Pinehurst Circle Tenleytown-AU station | Sibley Hospital | Nebraska Avenue NW | Monday-Friday service only. | M6 | Fairfax Village Line | Local | Fairfax Village (Alabama & Pennsylvania Avs SE) | Potomac Avenue station | Pennsylvania Avenue SE Alabama Avenue SE Southern Avenue | | Formerly known as the W6 until the early/mid-1990s N2, N3, N4, N6 | Massachusetts Avenue Line | Local | Friendship Heights station | N2, N4, N6 Farragut Square N3 Federal Triangle (Constitution Av & 10th St NW) | Western Avenue (N3, N4, N6) Wisconsin Avenue (N2) Massachusetts Avenue New Mexico Avenue NW (N2, N6) Connecticut Avenue NW | N3: weekday peak hour service only (N3: AM to Federal Triangle, PM to Friendship Heights) N2 & N4: Monday-Friday service only. N6 is a combination of the N2 and N4, operates post PM rush hour weekdays and all day on weekends. | N3 was part of the Massachusetts Av-Federal Triangle Line (along with the former N1) until 1996, when N1 was eliminated & N3 merged with the N2, N4 & N6. N4 used to terminate at Westmoreland Circle until the late 1990s. P6 | Anacostia-Eckington Line | Local* | Anacostia station | Archives (10th St & Pennsylvania Ave. NW) (P6) Rhode Island Avenue – Brentwood station (P6) | 11th Street Bridge New York Avenue NW (P6), 4th Street NE (P6) | Early AM/Late PM P6 terminate at Archives. Fare: $1 (south of the 11th Street Bridge, unless transferring to another bus) | P4, P5 & P6 were created to replace the A routes in 1991 when Anacostia station opened, with P5 & P6 additionally replacing the B6 between Metro Center & Rhode Island Avenue stations. P4 & P5 later merged with the P6, giving it the current route. S1 | 16th Street-Potomac Park Line | Local | 16th Street & Colorado Avenue NW | Potomac Park (Virginia Av & E St NW) | 16th Street NW 18th Street NW (to 16th & Colorado) 19th Street NW (to Potomac Park) | Weekday peak hour service only (AM to Potomac Park, PM to 16th & Colorado) | S2, S4 | 16th Street Line | Local | Silver Spring station* | Federal Triangle (10th St & Constitution Av NW) | Alaska Avenue NW (S2) 16th Street NW | Some S2 trips originate at 14th Street & Missouri Avenue NW going to Federal Triangle (peak hour only). Some northbound S2 trips terminate at 16th Street and Colorado Avenue NW (peak hour only). Silver Spring terminus is located on Wayne Avenue until completion of the Paul S. Sarbanes Transit Center. | All S4 weekday non-rush trips were truncated to Franklin Square (I & 13th Streets NW) on June 17, 2012. All S4 trips on the weekends through 7pm were also truncated to Franklin Square on December 30, 2012. S9 | 16th Street MetroExtra Line | Limited Stop | Silver Spring (Colesville Road & East-West Highway) | McPherson Square station (Franklin Square Entrance) | 16th Street NW | Weekday peak hour service only. | S9 was introduced in 2009, replacing the former S3 & S5 lines that were discontinued in the late 1990s. U2 | Minnesota Avenue-Anacostia Line | Local* | Minnesota Avenue station | Anacostia station | Minnesota Avenue NE/SE | Monday-Saturday service only. Fare: $1 (south of Good Hope Road & Minnesota Av SE, unless transferring to another bus) | Saturday service began in late 2011 U4 | Sheriff Road-River Terrace Line | Local | River Terrace and Mayfair | Minnesota Avenue station | Sheriff Road NE Minnesota Avenue NE Benning Road NE | order of terminals (north to south): River Terrace to Minnesota Avenue then Minnesota Avenue to Sheriff Road NE, then reverse. | Formerly known as the M16 (Metro \Mini-Bus\")" U5, U6 | Mayfair-Marshall Heights Line | Local | U5, U6 Marshall Heights U6 Mayfair | Minnesota Avenue station | Minnesota Avenue NE/SE Texas Avenue SE | U6: order of terminals: Marshall Heights to Minnesota Avenue then Minnesota Avenue to Mayfair, then reverse. | Runs on a portion of the old M16 (Metro \Mini-Bus\")" U8 | Capitol Heights-Benning Heights Line | Local | Capitol Heights station and Benning Heights (H St & 45th Place SE) | Minnesota Avenue station | Nannie Helen Burroughs Avenue NE Benning Road NE/SE | order of terminals (east to west): Capitol Heights to Minnesota Avenue then Minnesota Avenue to Benning Heights, then reverse. | U8 was created to replace the former X2, X4 & X6 routes east of Minnesota Avenue station in the late 1990s (X2 to Capitol Heights station, X4 then X6 to Benning Heights) V5 | Fairfax Village-L'Enfant Plaza Line | Local | Fairfax Village (Alabama Ave & 38th St SE) | L'Enfant Plaza station (E & 7th Streets SW) | Alabama Avenue SE Good Hope Road SE SW/SE Freeway | Weekday peak hour service only (AM to L'Enfant Plaza, PM to Fairfax Village) | V7, V8, V9 | Minnesota Avenue-M Street Line | Local | V7, V8 Deanwood station V9 Benning Heights (H St & 45th Pl SE) | V7 Bureau of Engraving V8 Archives (9th St & Pennsylvania Av NW) V9 Navy Yard – Ballpark | Minnesota Avenue NE/SE M Street SE/SW 7th Street SW/NW (V8) | V8: weekend service only V9: weekday peak hour service only (AM to Navy Yard - Ballpark Station, PM to Benning Heights) Late night V7 trips from Deanwood end at Navy Yard – Ballpark station. | V7 was created to replace the combination of the former V4 & V6 routes in the late 1990s. The V6 carried over to operate alongside V7, V8 & V9 at their inception, but was eventually phased out within 5 years after the Half & O Streets SW portion of the route (also served by the 70) was eliminated in favor of 70's increased frequency in the area. On March 30, 2014 the V9 operates between Navy Yard - Ballpark Station & Benning Heights. W1 | Shipley Terrace-Fort Drum Line | Local | Fort Drum | Southern Avenue station | Alabama Avenue SE Martin Luther King Jr Avenue | W1: Monday-Friday service only. | W1 replace the M8, M9 on March 3, 2014. W2, W3 | United Medical Center-Anacostia Line | Local | United Medical Center | Washington Overlook (Mellon St & Martin Luther King Av SE) Anacostia station | Southern Avenue Alabama Avenue SE Morris Road SE Martin Luther King Avenue SE | W3: Monday-Friday service only. Fare: $1 (unless transferring to another bus) | (Portions of the W2 & W3 operate on the old M18 & M20 (Metro \Mini-Bus\") routes" W4 | Deanwood-Alabama Avenue Line | Local* | Deanwood station | Anacostia station | Kenilworth Avenue Division Avenue NE Benning Road SE Alabama Avenue SE & South Capitol Street | Some school day trips terminate at Martin Luther King & Malcolm X Avenues SE Fare: $1 (south of Congress Heights station unless transferring to another bus) | W4's original routing to Bolling Air Force Base was extended to Anacostia station in the early 2000s. W4 no longer operates between Capital Plaza and Deanwood Station as of March 24, 2013, when a portion of that route was discontinued. As a result, the W4 was truncated and now operates between Deanwood Station and Anacostia Station. The W5 now serves the former W4 stops at the Bolling AFB gates. W6, W8 | Garfield-Anacostia Loop Line | Local* | Garfield (Robinson Pl & Jasper Rd SE) | Anacostia station | Good Hope Road SE Alabama Avenue SE Stanton Road SE | W6: Clockwise loop W8: Counterclockwise loop Fare: $1 (unless transferring to another bus) | Portions of the W6 & W8 operate on the old M18 & M20 (The \Metro-Mini\" buses) routes" W9 | L'Enfant Plaza-Coast Guard Metro Extra Line | Limited Stop | L'Enfant Plaza Metrorail Station | Livingston Road & 3rd Street, SE | South Capitol St SW 7th St SW M St SW | Weekday Peak Hour Service Only Limited-Stop Service | W9 started service on August 5,2013 & on September 29, 2013 the route was extended from the Coast Guard HQ to Livingston. X1, X3 | Benning Road Line | Local | Minnesota Avenue station | X1 Foggy Bottom – GWU station X3 Tenleytown-AU station | Benning Road NE H Street NE (X1) Florida Avenue NE/NW (X3) Constitution Avenue NW (X1) Calvert Street NW (X3) | X1 & X3: weekday peak hour service only (AM to Foggy Bottom - GWU/McLean Gardens, PM to Minnesota Avenue). | X3 was discontinued for several years before it was brought back to service in 2004. X3 was extended to Tenleytown-AU station on December 30, 2012. X2 | Benning Road-H Street Line | Local | Minnesota Avenue station | Lafayette Square | Benning Road NE H Street NE/NW | Some PM peak hour trips originate from Ballou High School going to Minnesota Avenue station when the school is open. | The X2 originally operated to Capitol Heights station until the mid-1990s when the route east of Minnesota Avenue station (along with the X4 & X6 route south of the station) were replaced by the U8. X8 | Maryland Avenue Line | Local | Carver Terrace (21st Place & Maryland Av NE) | Union Station | Maryland Avenue NE | | X9 | Benning Road-H Street Metro Extra Line | Limited Stop | Capitol Heights station | Metro Center (12th Street & New York Avenue, NW) | Nannie Helen Borroughs Avenue NE Benning Road NE H Street NE/NW | Peak hour limited stop service only (AM to Metro Center, PM to Capitol Heights) | Formerly known as the East Capitol Street Express line that was discontinued in the late 1980s; reincarnated as the Benning Road-H Street Express Line in December 2010
WTQ_for_TSD
Route | Name | Fare Type | Terminals | Terminals | Major streets | Notes | History 31 | Wisconsin Avenue Line | Local | Friendship Heights station | Potomac Park (Virginia Av & 21st St NW) | Wisconsin Avenue NW | | 31 replaces the Wisconsin Avenue portion of the old 30 (see Pennsylvania Avenue Line) 32, 36 | Pennsylvania Avenue Line | Local | Friendship Heights station | 32 Southern Avenue station 36 Naylor Road station | Wisconsin Avenue NW Pennsylvania Avenue SE/NW Branch Avenue SE (36) Alabama Avenue SE (32) | Some weekday 32 and 36 trips terminate at: Farragut Square Foggy Bottom – GWU station | 36 replaces a portion of the old 35 (see Pennsylvania Avenue Line) 34 | Naylor Rd Line | Local | Archives (10th St & Pennsylvania Av NW) | Naylor Road station | Pennsylvania Avenue SE Independence Avenue SE/SW Naylor Road SE | | 34 operated to Friendship Heights station until replaced by the M5, which operated from Naylor Road station to Eastern Market station in 2007; 34 replaced the M5 in 2008 with the extension to the Archives station, also see Pennsylvania Avenue Line 37 | Wisconsin Avenue Metro Extra Line | Limited Stop | Friendship Heights station | Archives station (AM End) Federal Triangle (10th St & Pennsylvania Av NW) (PM Start) | Wisconsin Avenue NW Massachusetts Avenue NW Pennsylvania Avenue NW | Weekday peak hour service only (AM to Archives, PM to Friendship Heights) Limited Stops Only | A prior \incarnation\" of the 37 was once known as the Wisconsin Avenue Express Line | running from Tenleytown-AU station to Archives until the early 1990s" 39 | Pennsylvania Avenue Metro Extra Line | Limited Stop | Naylor Road station | Potomac Park (Virginia Av & 21st St NW) | Pennsylvania Avenue SE/NW | Weekday peak hour service only AM to Potomac Park, PM to Naylor Road Limited Stops Only | 42, 43 | Mount Pleasant Line | Local | Mount Pleasant (Mount Pleasant & Lamont Streets NW) | 42 Gallery Place station 43 Farragut Square (AM End) 43 McPherson Square station (Franklin Square Entrance) (PM Start) | 42 Mount Pleasant Street NW, Columbia Road NW, Connecticut Avenue NW, H/I Streets NW 43 Mount Pleasant Street NW, Columbia Road NW, Connecticut Avenue NW | 42 serves Dupont Circle station some peak hour trips terminate at Farragut Square 43: weekday peak hour service only Travels underneath Dupont Circle via the Connecticut Avenue underpass) | See Mount Pleasant Line 52, 53, 54 | 14th Street Line | Local | Takoma station 14th Street & Colorado Ave NW | 52, 54 L'Enfant Plaza Metrorail Station (7th & D Streets SW) 53 McPherson Square station (Franklin Square Entrance) | 14th Street NW Pennsylvania Avenue NW (54) Independence Avenue SW (52) | 52 and 54: daily 53: Monday-Saturday only | 52 & 54 originally terminated at Navy Yard until the mid-1990s, when the 52 was truncated to L'Enfant Plaza station & 54 to Federal Triangle. 54 was later extended to L'Enfant Plaza station. The 53 was introduced several years after the former route 50 was discontinued, operating at first to Bureau Of Engraving before being shortened to Federal Triangle and now to Franklin Square. Also see 14th Street Line 62, 63 | Takoma-Petworth Line | Local | Takoma station | 62 Georgia Avenue – Petworth station 63 Federal Triangle (10th St & Constitution Av NW) | 5th Street NW, Kansas Avenue NW, Sherman Avenue NW (63) 13th Street NW (63) | 63: weekday peak & early weekend AM hours only | 63 operates through the portion of the 62 that operated to Federal Triangle until Georgia Avenue – Petworth station opened in 1999; it also replaces the 68, which operated from Georgia Avenue – Petworth station to Federal Triangle from 2001–2009 60, 64 | Fort Totten-Petworth Line | Local | Fort Totten station | 60 Georgia Avenue – Petworth station 64 Federal Triangle (10th St & Constitution Av NW) | Rock Creek Church Rd NW (60) Upshur Street NW (60) New Hampshire Avenue NW (64) 11th Street NW (64) | 60: Monday-Friday service only | 64 was replaced by the 66 south of Georgia Avenue – Petworth station when it opened in 1999; it replaced the 66 in 2009 64 also runs on the old 11th Street Streetcar Line. 70 | Georgia Avenue-7th Street Line | Local | Silver Spring station* | Archives station | Georgia Avenue NW 7th Street NW | Silver Spring terminus is located on Wayne Avenue until completion of the Paul S. Sarbanes Transit Center. | See Seventh Street Line Starting September 23, 2011, 71 service was discontinued, and the 70 was shortened to Archives. For service to Southwest Waterfront, see route directly below this one. 74 | Convention Center-Southwest Waterfront Line | Local | Mount Vernon Square (K & 6th Streets NW) | Half & O Streets SW, or Buzzard Point (2nd & V Streets SW) | 7th Street NW/SW | Serves Buzzard Point during rush hour only | Introduced September 24, 2011 as a replacement of DC Circulator's discontinued Convention Center-Southwest Waterfront route, and to also serve the southern portion of the 70 and 71 routes. 79 | Georgia Avenue Metro Extra Line | Limited Stop | Silver Spring station* | Archives station | Georgia Avenue NW, 7th Street NW (to Silver Spring), 9th Street NW (to Archives) | limited-stop service Silver Spring terminus is located on Wayne Avenue until completion of the Paul S. Sarbanes Transit Center | 79 is a \reincarnation\" of the old 73 (Brightwood Express Line) that was discontinued roughly a decade before the 79's introduction in 2006. Saturday service began on March 24 | 2013. Sunday service began on December 29 | 2013." 80 | North Capitol Street Line | Local | Fort Totten station | Kennedy Center | 12th Street NE Michigan Avenue NE North Capitol Street H Street NW K Street NW | some peak hour and early AM/late night trips terminate at McPherson Square station | 80 operates on the old North Capitol Street Streetcar Line, which operated from Washington Circle to Brookland until 1958 It operated to Potomac Park until it replaced the portion of the old Route 81 south of Pennsylvania Avenue NW to Kennedy Center after it was discontinued in the mid-1990s 90, 92, 93 | U Street-Garfield Line | Local* | Duke Ellington Bridge or Frank D. Reeves Center (14th & U Streets NW) | 90 Anacostia station 92 Congress Heights station 93 Congress Heights station | Calvert Street NW U Street NW, Florida Avenue NW/NE 8th Street NE Good Hope Road SE (92) Stanton Road SE (93) | 93: operates when Metrorail is not open, replacing the 90 & 94 Fare: $1 (90 only, south of the 11th Street Bridge, unless transferring to another bus) | 90 replaced all portions of the 94 north of Anacostia station which became the 94's northern terminal after it opened in 1991; 90, 92, and 93 served McLean Gardens from the mid-1990s to the mid-2000s until replaced by the 96. Also see U Street Line, New Jersey Avenue Line and Florida Avenue Line 94 | Stanton Road Line | Local* | Stanton Road (19th & Savannah Streets SE) | Anacostia station | Stanton Road SE | replaced by 93 (U Street-Garfield Line) when not in operation Fare: $1 (unless transferring to another bus) | 94 used to operate to Duke Ellington Bridge (as part of the U Street-Garfield Line) until Anacostia station opened in 1991; replaced by the 90 north of Anacostia since then. 96, 97 | East Capitol Street-Cardozo Line | Local | Capitol Heights station | 96 Tenleytown-AU station 97 Union Station | East Capitol Street New Jersey Avenue NW (96) U Street NW (96) 29th Street NW (96) | 96 operates between Stadium-Armory and Tenleytown-AU stations when the 97 operates during the weekday peak hours only 97 skips DC General Health Campus. | Formerly known as the New Jersey Avenue Line 96 & 97 replaced the old Routes 40 & 44 east of Union Station in the mid-1990s. 96 extended from Duke Ellington Bridge to McLean Gardens in the mid-2000s, replacing the northwestern portion of the 90, 92, and 93. 96 was extended to Tenleytown-AU station December 30, 2012. A2, A6, A7, A8, A42, A46, A48 | Anacostia-Congress Heights Line | Local* | Southern Avenue station (A2, A42) Livingston Rd & 3rd Street SE (A6, A8, A46, A48) Southern Avenue & South Capitol Street, SE (A7) | Anacostia Station (A2, A6, A7, A8) Archives station (10th St & Pennsylvania Av NW) (A42, A46, A48) | Martin Luther King Avenue SE, Mississippi Av SE (A2, A42) Wheeler Road SE (A6, A7, A46) South Capitol Street (A8, A48) | A7: weekday peak hour service only (AM to Anacostia, PM to Livingston Road) A42, A46 and A48 operate when Metrorail is closed, replacing A2, A6, A8 (respectively) and P2*Fare: $1 (unless transferring to another bus; A42, A46, A48: south of 11th Street Bridge) | Formerly known as the Anacostia Line (along with A4 & A5) until 1991 A7 operated to L'Enfant Plaza station until Anacostia opened in 1991 A42, A46 and A48 replaced the old portions of the A2, A6 and A8 north of Anacostia station to Archives when Anacostia opened A4, W5 | Anacostia-Fort Drum Line | Local* | D.C. Village (North Parking Lot) | Anacostia station St. Elizabeth's Gate 4 (Coast Guard HQ) | Martin Luther King Avenue SE South Capitol Street | W5: weekday peak hour service only (AM to DC Village, PM to Anacostia via the Blue Plains Facility) Fare: $1 (unless transferring to another bus) A4, W5 runs to St. Elizabeth's Gate 4 (Coast Guard HQ) to D.C. Village (North Parking Lot)Weekdays Only. | A4 and A5 operated to Archives station (as part of the Anacostia Line) until Anacostia opened in 1991 The route north of Anacostia is now served by P6 The A5 covered the A4 route but excluded Fort Drum. It was discontinued on March 24, 2013, replaced by the W5 which runs on South Capitol Street (SB) and DC-295 (NB). A9 | Martin Luther King Jr Ave MetroExtra Line | Limited Stop | Livingston Road & 3rd Street, SE | McPherson Square station (Franklin Square Entrance) | Martin Luther King Jr Ave | A9: weekday MetroExtra Peak Hour service only (AM to McPherson Square, PM to Livingston Road) Limited Stops Only | A9 is now a MetroExtra Bus service as of March 24, 2013. B2 | Bladensburg Road-Anacostia Line | Local* | Mount Rainier Terminal (Rhode Island Ave & 34th Street) | Anacostia station | Bladensburg Road NE 14th Street NE (to Anacostia) 15th Street NE (to Mount Rainier) Minnesota Avenue SE | Some trips terminate at Bladensburg Road & V Street NE some PM peak hour trips start at Potomac Avenue station on school days only Fare: $1 (south of the 11th Street Bridge unless transferring to another bus) | B2 used to operate to 16th & W Streets, SE in Anacostia until Anacostia station opened in 1991 B2 then covered the portion of the old B4 & B5 routes to Barry Farms after the station opened B8, B9 | Fort Lincoln Shuttle Line | Local | B8 Fort Lincoln (Petersburg Apartments) B9 Colmar Manor (40th Place & Bladensburg Road) | Rhode Island Avenue – Brentwood station | Bladensburg Road (B9) Franklin Street NE Rhode Island Avenue NE | B8: Monday-Friday service only, except middays B9: Monday-Friday midday service only | D1 | Glover Park-Federal Triangle Line | Local | Glover Park (41st St & Davis Pl NW) | Federal Triangle (10th St & Constitution Av NW) | Q Street NW K Street NW 13th Street NW | weekday peak hour service only (AM to Federal Triangle, PM to Glover Park) | D1 operated to Union Station/Ivy City until redirected to Federal Triangle in 2010 D2 | Glover Park-Dupont Circle Line | Local | Glover Park (41st St & Davis Pl NW) | Dupont Circle station (20th & Q Sts NW Entrance) | Q Street NW | | D2 operated to Stadium-Armory station (as part of the Glover Park-Trinidad Line) until replaced by the D6 east of Dupont Circle in the mid-1990s D3 | Ivy City-Dupont Circle Line | Local | Ivy City (New York Avenue & Fenwick Street NE) | Georgetown (35th Street & Reservoir Road NW) (AM End) Dupont Circle (20th St & Massachusetts Av NW) (PM Start) | Q Street NW (to Reservoir Road) K Street NW/NE E Street NW | D3 operates weekday peak hours only (AM to Reservoir Road, PM to Ivy City) | D3 operated between Sibley Hospital and Union Station (with select peak hour service from Ivy City) until 2010 when the D1 was rerouted to Federal Triangle D4 | Ivy City-Franklin Square Line | Local | Ivy City (New York Avenue & Fenwick Street NE) | McPherson Square station (Franklin Square Entrance) | K Street NW/NE | | D4 at first operated to Sibley Hospital (as part of the Glover Park-Trinidad Line) until replaced by D6 in the mid-1990s It then operated to Union Station (as the Ivy City-Union Station Line) until 2010, when it was extended to Franklin Square D5 | MacArthur Boulevard-Georgetown Line | Local | Little Flower Church (Bethesda, MD) | Farragut Square | MacArthur Boulevard NW M Street NW Pennsylvania Avenue NW | Operates weekday peak hours only (AM to Farragut Square, PM to Little Flower Church). | Formerly known as the MacArthur Boulevard-M Street Line (with the former D9, which was discontinued in the mid-1990s) D6 | Sibley Hospital-Stadium Armory Line | Local | Sibley Hospital | Stadium-Armory station (North Entrance) | MacArthur Boulevard NW Q Street NW K Street NW E Street NW C Street NE (to Stadium-Armory) D Street NE (to Sibley Hospital) | | D6 originally operated between Glover Park & Washington Hospital Center (as part of the Glover Park-Trinidad Line) until the mid-1990s, when it was rerouted to serve Sibley Hospital (replacing the truncated D4 & D8 west of Union Station and Stadium-Armory (replacing the truncated 42 & D2 east of Dupont Circle. D8 | Hospital Center Line | Local | Washington Hospital Center | Union Station | Franklin Street NE Brentwood Road NE Mount Olivet Rd NE K Street NE | Some trips end at Rhode Island Avenue – Brentwood station during the PM peak hour period | D8 operated to Sibley Hospital (as part of the Glover Park-Trinidad Line) until replaced by the D6 (west of Union Station) in the mid-1990s E2, E3, E4 | Military Road-Crosstown Line | Local | Friendship Heights station | E2 Fort Totten station E2, E3 Ivy City (New York Av & Fenwick St NE) E4 Riggs Park (Eastern Av & Jamaica St NE) | Military Road Kennedy Street South Dakota Avenue (E2, E3) 18th Street NE (E2, E3) | E2 terminates at Fort Totten station when E3 is in operation (weekends only) E3 also serves Riggs Park (it is a combination of the E2 and E4) | E6 | Chevy Chase Line | Local | Knollwood (Knollwood Retirement Home) | Friendship Heights station | Western Avenue McKinley Street NW | | G2 | P Street-LeDroit Park Line | Local | Georgetown University (37th & O Streets NW) | LeDroit Park (Bryant & 4th Streets NW) | P Street NW | | G8 | Rhode Island Avenue Line | Local | Avondale (Eastern & Michigan Avs NE) | Farragut Square | Monroe Street NE Rhode Island Avenue NW/NE 9th Street NW (to Farragut Square) 11th Street NW (to Avondale) H Street NW | Some trips operate from Brookland-CUA station to Avondale during weekday PM peak hours | G8 is a combination of the old G4 & G6 that operated to Lafayette Square (G4) & Gallery Place station (G6) until the mid-1990s H1 | Brookland-Potomac Park Line | Local | Brookland-CUA station | Potomac Park (17th & C Streets NW) | Michigan Avenue NW/NE Columbia Road NW 23rd Street NW | weekday peak hour service only (AM to Potomac Park, PM to Brookland) | H1 was discontinued in the mid-1990s until it was \reincarnated\" in 2006" H2, H3, H4 | Crosstown Line | Local | Tenleytown-AU station | Brookland-CUA station | Wisconsin Avenue Porter Street NW Van Ness/Veazey Street NW (H2) Connecticut Avenue (H2) Columbia Road NW/Irving Street NW Michigan Avenue NW/NE | H3: weekday peak hour service only H3: Skips Washington Hospital Center | H2 & H4 operated to Fort Lincoln (east of Brookland station) until replaced by H6 in the late 1990s. They also operated to Westmoreland Circle & Western Avenue NW (west of Tenleytown station) until replaced by the N8 in the late 1990s. H3's route west of Porter Street & Connecticut Avenue NW was served by H2 until it was rerouted to serve and terminate at Van Ness Station in the early 2000s. H2 was later rerouted back to its Tenleytown terminus, replacing the N8 route east of Tenleytown and rerouting the H3 to serve exactly the same route as the H4 with the exception of Washington Hospital Center. H6 | Brookland-Fort Lincoln Line | Local | Fort Lincoln (Petersburg Apartments) | Brookland-CUA station | Franklin Street NE 14th Street NE | | H6 covers the route covered by the H2 & H4 between Brookland station & Fort Lincoln until the late 1990s H8, H9 | Park Road-Brookland Line | Local | H8 Mount Pleasant (Mount Pleasant & 17th Streets NW) H9 Archbishop Carroll High School | Rhode Island Avenue – Brentwood station | Irving Street NW (H8) Rock Creek Church Road NW (H8) 10th Street NE 12th Street NE | H9 only operates when Carroll High School is open Some H8 trips operate from Rock Creek Church Rd & Upshur Street NW to Columbia Heights station during the PM peak hours when public schools are open | K2 | Takoma-Fort Totten Line | Local | Takoma station | Fort Totten station | North Capitol Street Kansas Avenue NE Eastern Avenue | Weekday peak hour service only | K2 operated to Walter Reed Army Medical Center until 2005, when it was replaced by K1 north of Takoma station. L1, L2 | Connecticut Avenue Line | Local | Chevy Chase Circle | L1 Potomac Park (17th & C Streets NW) L2 McPherson Square station | Connecticut Avenue NW Calvert Street NW (L2) 18th Street NW (L2) 23rd Street NW (L1) K Street NW (L2) | L1 weekday peak hour service only (AM to Potomac Park, PM to Chevy Chase Circle) | M4 | Nebraska Avenue Line | Local | Pinehurst Circle Tenleytown-AU station | Sibley Hospital | Nebraska Avenue NW | Monday-Friday service only. | M6 | Fairfax Village Line | Local | Fairfax Village (Alabama & Pennsylvania Avs SE) | Potomac Avenue station | Pennsylvania Avenue SE Alabama Avenue SE Southern Avenue | | Formerly known as the W6 until the early/mid-1990s N2, N3, N4, N6 | Massachusetts Avenue Line | Local | Friendship Heights station | N2, N4, N6 Farragut Square N3 Federal Triangle (Constitution Av & 10th St NW) | Western Avenue (N3, N4, N6) Wisconsin Avenue (N2) Massachusetts Avenue New Mexico Avenue NW (N2, N6) Connecticut Avenue NW | N3: weekday peak hour service only (N3: AM to Federal Triangle, PM to Friendship Heights) N2 & N4: Monday-Friday service only. N6 is a combination of the N2 and N4, operates post PM rush hour weekdays and all day on weekends. | N3 was part of the Massachusetts Av-Federal Triangle Line (along with the former N1) until 1996, when N1 was eliminated & N3 merged with the N2, N4 & N6. N4 used to terminate at Westmoreland Circle until the late 1990s. P6 | Anacostia-Eckington Line | Local* | Anacostia station | Archives (10th St & Pennsylvania Ave. NW) (P6) Rhode Island Avenue – Brentwood station (P6) | 11th Street Bridge New York Avenue NW (P6), 4th Street NE (P6) | Early AM/Late PM P6 terminate at Archives. Fare: $1 (south of the 11th Street Bridge, unless transferring to another bus) | P4, P5 & P6 were created to replace the A routes in 1991 when Anacostia station opened, with P5 & P6 additionally replacing the B6 between Metro Center & Rhode Island Avenue stations. P4 & P5 later merged with the P6, giving it the current route. S1 | 16th Street-Potomac Park Line | Local | 16th Street & Colorado Avenue NW | Potomac Park (Virginia Av & E St NW) | 16th Street NW 18th Street NW (to 16th & Colorado) 19th Street NW (to Potomac Park) | Weekday peak hour service only (AM to Potomac Park, PM to 16th & Colorado) | S2, S4 | 16th Street Line | Local | Silver Spring station* | Federal Triangle (10th St & Constitution Av NW) | Alaska Avenue NW (S2) 16th Street NW | Some S2 trips originate at 14th Street & Missouri Avenue NW going to Federal Triangle (peak hour only). Some northbound S2 trips terminate at 16th Street and Colorado Avenue NW (peak hour only). Silver Spring terminus is located on Wayne Avenue until completion of the Paul S. Sarbanes Transit Center. | All S4 weekday non-rush trips were truncated to Franklin Square (I & 13th Streets NW) on June 17, 2012. All S4 trips on the weekends through 7pm were also truncated to Franklin Square on December 30, 2012. S9 | 16th Street MetroExtra Line | Limited Stop | Silver Spring (Colesville Road & East-West Highway) | McPherson Square station (Franklin Square Entrance) | 16th Street NW | Weekday peak hour service only. | S9 was introduced in 2009, replacing the former S3 & S5 lines that were discontinued in the late 1990s. U2 | Minnesota Avenue-Anacostia Line | Local* | Minnesota Avenue station | Anacostia station | Minnesota Avenue NE/SE | Monday-Saturday service only. Fare: $1 (south of Good Hope Road & Minnesota Av SE, unless transferring to another bus) | Saturday service began in late 2011 U4 | Sheriff Road-River Terrace Line | Local | River Terrace and Mayfair | Minnesota Avenue station | Sheriff Road NE Minnesota Avenue NE Benning Road NE | order of terminals (north to south): River Terrace to Minnesota Avenue then Minnesota Avenue to Sheriff Road NE, then reverse. | Formerly known as the M16 (Metro \Mini-Bus\")" U5, U6 | Mayfair-Marshall Heights Line | Local | U5, U6 Marshall Heights U6 Mayfair | Minnesota Avenue station | Minnesota Avenue NE/SE Texas Avenue SE | U6: order of terminals: Marshall Heights to Minnesota Avenue then Minnesota Avenue to Mayfair, then reverse. | Runs on a portion of the old M16 (Metro \Mini-Bus\")" U8 | Capitol Heights-Benning Heights Line | Local | Capitol Heights station and Benning Heights (H St & 45th Place SE) | Minnesota Avenue station | Nannie Helen Burroughs Avenue NE Benning Road NE/SE | order of terminals (east to west): Capitol Heights to Minnesota Avenue then Minnesota Avenue to Benning Heights, then reverse. | U8 was created to replace the former X2, X4 & X6 routes east of Minnesota Avenue station in the late 1990s (X2 to Capitol Heights station, X4 then X6 to Benning Heights) V5 | Fairfax Village-L'Enfant Plaza Line | Local | Fairfax Village (Alabama Ave & 38th St SE) | L'Enfant Plaza station (E & 7th Streets SW) | Alabama Avenue SE Good Hope Road SE SW/SE Freeway | Weekday peak hour service only (AM to L'Enfant Plaza, PM to Fairfax Village) | V7, V8, V9 | Minnesota Avenue-M Street Line | Local | V7, V8 Deanwood station V9 Benning Heights (H St & 45th Pl SE) | V7 Bureau of Engraving V8 Archives (9th St & Pennsylvania Av NW) V9 Navy Yard – Ballpark | Minnesota Avenue NE/SE M Street SE/SW 7th Street SW/NW (V8) | V8: weekend service only V9: weekday peak hour service only (AM to Navy Yard - Ballpark Station, PM to Benning Heights) Late night V7 trips from Deanwood end at Navy Yard – Ballpark station. | V7 was created to replace the combination of the former V4 & V6 routes in the late 1990s. The V6 carried over to operate alongside V7, V8 & V9 at their inception, but was eventually phased out within 5 years after the Half & O Streets SW portion of the route (also served by the 70) was eliminated in favor of 70's increased frequency in the area. On March 30, 2014 the V9 operates between Navy Yard - Ballpark Station & Benning Heights. W1 | Shipley Terrace-Fort Drum Line | Local | Fort Drum | Southern Avenue station | Alabama Avenue SE Martin Luther King Jr Avenue | W1: Monday-Friday service only. | W1 replace the M8, M9 on March 3, 2014. W2, W3 | United Medical Center-Anacostia Line | Local | United Medical Center | Washington Overlook (Mellon St & Martin Luther King Av SE) Anacostia station | Southern Avenue Alabama Avenue SE Morris Road SE Martin Luther King Avenue SE | W3: Monday-Friday service only. Fare: $1 (unless transferring to another bus) | (Portions of the W2 & W3 operate on the old M18 & M20 (Metro \Mini-Bus\") routes" W4 | Deanwood-Alabama Avenue Line | Local* | Deanwood station | Anacostia station | Kenilworth Avenue Division Avenue NE Benning Road SE Alabama Avenue SE & South Capitol Street | Some school day trips terminate at Martin Luther King & Malcolm X Avenues SE Fare: $1 (south of Congress Heights station unless transferring to another bus) | W4's original routing to Bolling Air Force Base was extended to Anacostia station in the early 2000s. W4 no longer operates between Capital Plaza and Deanwood Station as of March 24, 2013, when a portion of that route was discontinued. As a result, the W4 was truncated and now operates between Deanwood Station and Anacostia Station. The W5 now serves the former W4 stops at the Bolling AFB gates. W6, W8 | Garfield-Anacostia Loop Line | Local* | Garfield (Robinson Pl & Jasper Rd SE) | Anacostia station | Good Hope Road SE Alabama Avenue SE Stanton Road SE | W6: Clockwise loop W8: Counterclockwise loop Fare: $1 (unless transferring to another bus) | Portions of the W6 & W8 operate on the old M18 & M20 (The \Metro-Mini\" buses) routes" W9 | L'Enfant Plaza-Coast Guard Metro Extra Line | Limited Stop | L'Enfant Plaza Metrorail Station | Livingston Road & 3rd Street, SE | South Capitol St SW 7th St SW M St SW | Weekday Peak Hour Service Only Limited-Stop Service | W9 started service on August 5,2013 & on September 29, 2013 the route was extended from the Coast Guard HQ to Livingston. X1, X3 | Benning Road Line | Local | Minnesota Avenue station | X1 Foggy Bottom – GWU station X3 Tenleytown-AU station | Benning Road NE H Street NE (X1) Florida Avenue NE/NW (X3) Constitution Avenue NW (X1) Calvert Street NW (X3) | X1 & X3: weekday peak hour service only (AM to Foggy Bottom - GWU/McLean Gardens, PM to Minnesota Avenue). | X3 was discontinued for several years before it was brought back to service in 2004. X3 was extended to Tenleytown-AU station on December 30, 2012. X2 | Benning Road-H Street Line | Local | Minnesota Avenue station | Lafayette Square | Benning Road NE H Street NE/NW | Some PM peak hour trips originate from Ballou High School going to Minnesota Avenue station when the school is open. | The X2 originally operated to Capitol Heights station until the mid-1990s when the route east of Minnesota Avenue station (along with the X4 & X6 route south of the station) were replaced by the U8. X8 | Maryland Avenue Line | Local | Carver Terrace (21st Place & Maryland Av NE) | Union Station | Maryland Avenue NE | | X9 | Benning Road-H Street Metro Extra Line | Limited Stop | Capitol Heights station | Metro Center (12th Street & New York Avenue, NW) | Nannie Helen Borroughs Avenue NE Benning Road NE H Street NE/NW | Peak hour limited stop service only (AM to Metro Center, PM to Capitol Heights) | Formerly known as the East Capitol Street Express line that was discontinued in the late 1980s; reincarnated as the Benning Road-H Street Express Line in December 2010
Provide me with the row number and column number for the table shown in this image. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_267
WTQ_203-csv_542.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> № | # | Title | Directed by | Written by | Original air date | Production code 1 | 1 | \Class of Beverly Hills\"" | Tim Hunter | Darren Star | October 4, 1990 | – 2 | 2 | \The Green Room\"" | Michael Uno | David Stenn | October 11, 1990 | 2190001 3 | 3 | \Every Dream Has Its Price (Tag)\"" | Catlin Adams | Amy Spies | October 18, 1990 | 2190002 4 | 4 | \The First Time\"" | Bethany Rooney | Darren Star | October 25, 1990 | 2190003 5 | 5 | \One on One\"" | Artie Mandelberg | Charles Rosin | November 1, 1990 | 2190004 6 | 6 | \Higher Education\"" | Artie Mandelberg | Jordan Budde | November 15, 1990 | 2190005 7 | 7 | \Perfect Mom\"" | Bethany Rooney | Darren Star | November 22, 1990 | 2190006 8 | 8 | \The 17-Year Itch\"" | Jefferson Kibbee | Amy Spies | November 29, 1990 | 2190007 9 | 9 | \The Gentle Art of Listening\"" | Dan Attias | Charles Rosin | December 6, 1990 | 2190008 10 | 10 | \Isn't it Romantic?\"" | Nancy Malone | Charles Rosin | January 3, 1991 | 2190009 11 | 11 | \B.Y.O.B.\"" | Miles Watkins | Jordan Budde | January 10, 1991 | 2190010 12 | 12 | \One Man and a Baby\"" | Burt Brinckerhoff | Amy Spies | January 24, 1991 | 2190011 13 | 13 | \Slumber Party\"" | Charles Braverman | Darren Star | January 31, 1991 | 2190012 14 | 14 | \East Side Story\"" | Dan Attias | Charles Rosin | February 14, 1991 | 2190013 15 | 15 | \A Fling in Palm Springs\"" | Jefferson Kibbee | Jordan Budde | February 21, 1991 | 2190014 16 | 16 | \Fame is Where You Find It\"" | Paul Schneider | Charles Rosin & Karen Rosin | February 28, 1991 | 2190015 17 | 17 | \Stand (Up) and Deliver\"" | Burt Brinckerhoff | Amy Spies | March 7, 1991 | 2190016 18 | 18 | \It's Only a Test\"" | Charles Braverman | Darren Star | March 28, 1991 | 2190017 19 | 19 | \April is the Cruelest Month\"" | Dan Attias | Steve Wasserman & Jessica Klein | April 11, 1991 | 2190018 20 | 20 | \Spring Training\"" | Burt Brinckerhoff | Charles Rosin | April 25, 1991 | 2190019 21 | 21 | \Spring Dance\"" | Darren Star | Darren Star | May 2, 1991 | 2190020 22 | 22 | \Home Again\"" | Charles Braverman | Amy Spies | May 9, 1991 | 2190021
WTQ_for_TSD
№ | # | Title | Directed by | Written by | Original air date | Production code 1 | 1 | \Class of Beverly Hills\"" | Tim Hunter | Darren Star | October 4, 1990 | – 2 | 2 | \The Green Room\"" | Michael Uno | David Stenn | October 11, 1990 | 2190001 3 | 3 | \Every Dream Has Its Price (Tag)\"" | Catlin Adams | Amy Spies | October 18, 1990 | 2190002 4 | 4 | \The First Time\"" | Bethany Rooney | Darren Star | October 25, 1990 | 2190003 5 | 5 | \One on One\"" | Artie Mandelberg | Charles Rosin | November 1, 1990 | 2190004 6 | 6 | \Higher Education\"" | Artie Mandelberg | Jordan Budde | November 15, 1990 | 2190005 7 | 7 | \Perfect Mom\"" | Bethany Rooney | Darren Star | November 22, 1990 | 2190006 8 | 8 | \The 17-Year Itch\"" | Jefferson Kibbee | Amy Spies | November 29, 1990 | 2190007 9 | 9 | \The Gentle Art of Listening\"" | Dan Attias | Charles Rosin | December 6, 1990 | 2190008 10 | 10 | \Isn't it Romantic?\"" | Nancy Malone | Charles Rosin | January 3, 1991 | 2190009 11 | 11 | \B.Y.O.B.\"" | Miles Watkins | Jordan Budde | January 10, 1991 | 2190010 12 | 12 | \One Man and a Baby\"" | Burt Brinckerhoff | Amy Spies | January 24, 1991 | 2190011 13 | 13 | \Slumber Party\"" | Charles Braverman | Darren Star | January 31, 1991 | 2190012 14 | 14 | \East Side Story\"" | Dan Attias | Charles Rosin | February 14, 1991 | 2190013 15 | 15 | \A Fling in Palm Springs\"" | Jefferson Kibbee | Jordan Budde | February 21, 1991 | 2190014 16 | 16 | \Fame is Where You Find It\"" | Paul Schneider | Charles Rosin & Karen Rosin | February 28, 1991 | 2190015 17 | 17 | \Stand (Up) and Deliver\"" | Burt Brinckerhoff | Amy Spies | March 7, 1991 | 2190016 18 | 18 | \It's Only a Test\"" | Charles Braverman | Darren Star | March 28, 1991 | 2190017 19 | 19 | \April is the Cruelest Month\"" | Dan Attias | Steve Wasserman & Jessica Klein | April 11, 1991 | 2190018 20 | 20 | \Spring Training\"" | Burt Brinckerhoff | Charles Rosin | April 25, 1991 | 2190019 21 | 21 | \Spring Dance\"" | Darren Star | Darren Star | May 2, 1991 | 2190020 22 | 22 | \Home Again\"" | Charles Braverman | Amy Spies | May 9, 1991 | 2190021
For the table shown in this image, can you tell me the row and column numbers of this table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_268
WTQ_203-csv_463.jpg
Please identify the row and column numbers of the table displayed in this image. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Year | Film | Role | Language | Notes 2008 | Moggina Manasu | Chanchala | Kannada | Filmfare Award for Best Actress - Kannada Karnataka State Film Award for Best Actress 2009 | Olave Jeevana Lekkachaara | Rukmini | Kannada | Innovative Film Award for Best Actress 2009 | Love Guru | Kushi | Kannada | Filmfare Award for Best Actress - Kannada 2010 | Krishnan Love Story | Geetha | Kannada | Filmfare Award for Best Actress - Kannada Udaya Award for Best Actress 2010 | Gaana Bajaana | Radhey | Kannada | 2011 | Hudugaru | Gayithri | Kannada | Nominated, Filmfare Award for Best Actress – Kannada 2012 | Alemari | Neeli | Kannada | 2012 | Breaking News | Shraddha | Kannada | 2012 | Addhuri | Poorna | Kannada | Udaya Award for Best Actress Nominated — SIIMA Award for Best Actress Nominated — Filmfare Award for Best Actress – Kannada 2012 | 18th Cross | Punya | Kannada | 2012 | Sagar | Kajal | Kannada | 2012 | Drama | Nandini | Kannada | 2013 | Kaddipudi | Uma | Kannada | 2013 | Dilwala | Preethi | Kannada | 2013 | Bahaddoor | Anjali | Kannada | Filming 2014 | Mr. & Mrs. Ramachari | | | Announced 2014 | Endendigu | | | Filming
WTQ_for_TSD
Year | Film | Role | Language | Notes 2008 | Moggina Manasu | Chanchala | Kannada | Filmfare Award for Best Actress - Kannada Karnataka State Film Award for Best Actress 2009 | Olave Jeevana Lekkachaara | Rukmini | Kannada | Innovative Film Award for Best Actress 2009 | Love Guru | Kushi | Kannada | Filmfare Award for Best Actress - Kannada 2010 | Krishnan Love Story | Geetha | Kannada | Filmfare Award for Best Actress - Kannada Udaya Award for Best Actress 2010 | Gaana Bajaana | Radhey | Kannada | 2011 | Hudugaru | Gayithri | Kannada | Nominated, Filmfare Award for Best Actress – Kannada 2012 | Alemari | Neeli | Kannada | 2012 | Breaking News | Shraddha | Kannada | 2012 | Addhuri | Poorna | Kannada | Udaya Award for Best Actress Nominated — SIIMA Award for Best Actress Nominated — Filmfare Award for Best Actress – Kannada 2012 | 18th Cross | Punya | Kannada | 2012 | Sagar | Kajal | Kannada | 2012 | Drama | Nandini | Kannada | 2013 | Kaddipudi | Uma | Kannada | 2013 | Dilwala | Preethi | Kannada | 2013 | Bahaddoor | Anjali | Kannada | Filming 2014 | Mr. & Mrs. Ramachari | | | Announced 2014 | Endendigu | | | Filming
Please identify the row and column numbers of the table displayed in this image. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_269
WTQ_204-csv_247.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> Place | Player | Country | Score | To par | Money ($) 1 | Ralph Guldahl | United States | 72-68-70-69=279 | –9 | 1,500 2 | Sam Snead | United States | 70-70-72-68=280 | –8 | 800 T3 | Billy Burke | United States | 69-72-71-70=282 | –6 | 550 T3 | Lawson Little | United States | 72-72-68-70=282 | –6 | 550 5 | Gene Sarazen | United States | 73-66-72-72=283 | –5 | 400 6 | Craig Wood | United States | 72-73-71-68=284 | –4 | 300 7 | Byron Nelson | United States | 71-69-72-75=287 | –1 | 250 8 | Henry Picard | United States | 71-71-76-71=289 | +1 | 175 9 | Ben Hogan | United States | 75-71-72-72=290 | +2 | 125 T10 | Ed Dudley | United States | 75-75-69-72=291 | +3 | 100 T10 | Toney Penna | United States | 72-75-72-72=291 | +3 | 100
WTQ_for_TSD
Place | Player | Country | Score | To par | Money ($) 1 | Ralph Guldahl | United States | 72-68-70-69=279 | –9 | 1,500 2 | Sam Snead | United States | 70-70-72-68=280 | –8 | 800 T3 | Billy Burke | United States | 69-72-71-70=282 | –6 | 550 T3 | Lawson Little | United States | 72-72-68-70=282 | –6 | 550 5 | Gene Sarazen | United States | 73-66-72-72=283 | –5 | 400 6 | Craig Wood | United States | 72-73-71-68=284 | –4 | 300 7 | Byron Nelson | United States | 71-69-72-75=287 | –1 | 250 8 | Henry Picard | United States | 71-71-76-71=289 | +1 | 175 9 | Ben Hogan | United States | 75-71-72-72=290 | +2 | 125 T10 | Ed Dudley | United States | 75-75-69-72=291 | +3 | 100 T10 | Toney Penna | United States | 72-75-72-72=291 | +3 | 100
This is a table picture. Can you figure out the row and column numbers for this particular table? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_270
WTQ_201-csv_30.jpg
Tell me the row and column numbers of the shown table. The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> Year | Title | Chart positions AU | Chart positions CA | Chart positions IE | Chart positions NL | Chart positions NZ | Chart positions UK | Chart positions US Hot 100 | Chart positions US Airplay | Chart positions US Alternative 1995 | \You Oughta Know\" A" | 4 | 20 | — | 11 | 25 | 22 | — | 13 | 1 1995 | \Hand in My Pocket\"" | 13 | 1 | — | — | 7 | 26 | — | 15 | 1 1996 | \Ironic\"" | 3 | 1 | 8 | 6 | 3 | 11 | 4 | 2 | 1 1996 | \You Learn\"" | 20 | 1 | — | 13 | — | 24 | 6 | 1 | 7 1996 | \Head Over Feet\"" | 12 | 1 | 11 | 33 | 27 | 7 | — | 3 | 25 1997 | \All I Really Want\"" | 40 | 2 | — | — | — | 59 | — | 65 | 14
WTQ_for_TSD
Year | Title | Chart positions AU | Chart positions CA | Chart positions IE | Chart positions NL | Chart positions NZ | Chart positions UK | Chart positions US Hot 100 | Chart positions US Airplay | Chart positions US Alternative 1995 | \You Oughta Know\" A" | 4 | 20 | — | 11 | 25 | 22 | — | 13 | 1 1995 | \Hand in My Pocket\"" | 13 | 1 | — | — | 7 | 26 | — | 15 | 1 1996 | \Ironic\"" | 3 | 1 | 8 | 6 | 3 | 11 | 4 | 2 | 1 1996 | \You Learn\"" | 20 | 1 | — | 13 | — | 24 | 6 | 1 | 7 1996 | \Head Over Feet\"" | 12 | 1 | 11 | 33 | 27 | 7 | — | 3 | 25 1997 | \All I Really Want\"" | 40 | 2 | — | — | — | 59 | — | 65 | 14
Tell me the row and column numbers of the shown table. The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_271
WTQ_200-csv_45.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> # | Office | Current Officer | May succeed to Governorship | | Governor of New Mexico | Susana Martinez 1 | Lieutenant Governor of New Mexico | John Sanchez 2 | Secretary of State of New Mexico | Dianna Duran 3 | President Pro Tempore of the Senate | Mary Kay Papen 4 | Speaker of the House of Representatives | W. Ken Martinez | May serve as Emergency Interim Successor | 4 | Attorney General of New Mexico | Gary King 5 | State Auditor | Hector Balderas 6 | State Treasurer | James B. Lewis 7 | Commissioner of Public Lands | Ray Powell 8 | Public Regulation Commission, Chair | Patrick Lyons 9 | Public Regulation Commissioner | Karen Montoya 10 | Public Regulation Commissioner | Valerie Espinoza 11 | Public Regulation Commissioner | Theresa Becenti–Aguilar 12 | Public Regulation Commissioner | Ben Hall
WTQ_for_TSD
# | Office | Current Officer | May succeed to Governorship | | Governor of New Mexico | Susana Martinez 1 | Lieutenant Governor of New Mexico | John Sanchez 2 | Secretary of State of New Mexico | Dianna Duran 3 | President Pro Tempore of the Senate | Mary Kay Papen 4 | Speaker of the House of Representatives | W. Ken Martinez | May serve as Emergency Interim Successor | 4 | Attorney General of New Mexico | Gary King 5 | State Auditor | Hector Balderas 6 | State Treasurer | James B. Lewis 7 | Commissioner of Public Lands | Ray Powell 8 | Public Regulation Commission, Chair | Patrick Lyons 9 | Public Regulation Commissioner | Karen Montoya 10 | Public Regulation Commissioner | Valerie Espinoza 11 | Public Regulation Commissioner | Theresa Becenti–Aguilar 12 | Public Regulation Commissioner | Ben Hall
This is a table picture. Can you figure out the row and column numbers for this particular table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_272
WTQ_203-csv_474.jpg
Please identify the row and column numbers of the table displayed in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Year | Name | Year | Name | Year | Name 1903-04 | Mr B. Owen- Jones | 1935-36 | Mr W.Pearce | 1967-68 | Mr J.F.Serfontein 1904-05 | Mr B. Owen- Jones | 1936-37 | Mr W.Pearce | 1968-69 | Mr Ben Steyn 1905-06 | Mr G. Constable | 1937 -38 | | 1969-70 | 1907-08 | Mr T.R.Ziervogel | 1939 -40 | Mr W.E.Vickers | 1971-72 | Mr Chris Smith 1908-09 | Mr T.R.Ziervogel | 1940-41 | Mr P.Venter | 1972-73 | Mr Ben Steyn 1909-10 | Mr J.Morris | 1941-42 | Mr P.Venter | 1973-74 | Mr Issy Kramer 1910-11 | | 1942-43 | Mr P.Venter | 1974-75 | 1911-12 | Mr B.Owen- Jones | 1943-44 | Mr P.Venter | 1975-76 | Mr Sakkie Blanche 1912-13 | Mr J.Johnston | 1944-45 | Mrs E.Myer | 1977-78 | Mr Sakkie Blanche 1913-14 | Mr J.Cook | 1945-46 | Mrs E.Myer | 1978-79 | 1914-15 | Mr J.Cook | 1946-47 | Mrs E.Myer | 1979 -80 | Mr Kobus Durand 1915-16 | Mr R.Champion | 1947-48 | Mr C.Chambers | 1980-81 | Mr Meyer 1916-17 | Mr R.Champion | 1948-49 | Mrs S.Von Wielligh | 1981-82 | Mr Wiek Steyn 1917-18 | Mr A.Ruffels | 1949-50 | Mr A.J.Law | 1982-83 | Mr Andrew Wheeler 1918-19 | Mr J.Campbell | 1950-51 | Mr P.Venter | 1983-84 | 1919-20 | Mr B.Melman | 1951-52 | Mr P.Venter | 1984-85 | 1920-21 | Mr B.Melman | 1952-53 | Mr Vic Pretorius | 1985-86 | Mr J.Prins 1921-21 | Mr B.Melman | 1953-54 | Mr Vic Pretorius | 1986-87 | 1922-23 | Mr J.Campbell | 1954-55 | | 1987-88 | 1923-24 | | 1954-56 | Mr J.H.A.Roets | 1988-89 | Mr Beyers De Klerk 1924-25 | Mr E.Murton | 1956-57 | Mr P.H.Tredoux | 1989-90 | Mr Gerrie Wolmarans 1925-26 | Mr S.Steenberg | 1957- 58 | | 1990-91 | Mr Gerrie Wolmarans 1926-27 | | 1958-59 | Mr J.M.Cawood | 1991-92 | Mr TJ Ferreira 1927-28 | Mr J.Stanbury | 1959-60 | Mr A.P.Scribante | 1992-93 | Mr Gerrie Wolmarans 1928-29 | Mr E.Murton | 1960-61 | Mr J.L.Viljoen | 1993-94 | Mr TJ Ferreira 1929-30 | Mr K.Turner | 1961-62 | Mr J.L.Viljoen | | 1930-31 | Mr J.E.Bigwood | 1962-63 | Mrs S.Von Wielligh | | 1931-32 | Mr A.Zaretsky | 1963-64 | Mr F.J.Van Heerden | | 1932-33 | Mr G.J.Malan | 1964-65 | | | 1933-34 | | 1965-66 | | | 1934-34 | | 1966-67 | Mr H.McLennan | |
WTQ_for_TSD
Year | Name | Year | Name | Year | Name 1903-04 | Mr B. Owen- Jones | 1935-36 | Mr W.Pearce | 1967-68 | Mr J.F.Serfontein 1904-05 | Mr B. Owen- Jones | 1936-37 | Mr W.Pearce | 1968-69 | Mr Ben Steyn 1905-06 | Mr G. Constable | 1937 -38 | | 1969-70 | 1907-08 | Mr T.R.Ziervogel | 1939 -40 | Mr W.E.Vickers | 1971-72 | Mr Chris Smith 1908-09 | Mr T.R.Ziervogel | 1940-41 | Mr P.Venter | 1972-73 | Mr Ben Steyn 1909-10 | Mr J.Morris | 1941-42 | Mr P.Venter | 1973-74 | Mr Issy Kramer 1910-11 | | 1942-43 | Mr P.Venter | 1974-75 | 1911-12 | Mr B.Owen- Jones | 1943-44 | Mr P.Venter | 1975-76 | Mr Sakkie Blanche 1912-13 | Mr J.Johnston | 1944-45 | Mrs E.Myer | 1977-78 | Mr Sakkie Blanche 1913-14 | Mr J.Cook | 1945-46 | Mrs E.Myer | 1978-79 | 1914-15 | Mr J.Cook | 1946-47 | Mrs E.Myer | 1979 -80 | Mr Kobus Durand 1915-16 | Mr R.Champion | 1947-48 | Mr C.Chambers | 1980-81 | Mr Meyer 1916-17 | Mr R.Champion | 1948-49 | Mrs S.Von Wielligh | 1981-82 | Mr Wiek Steyn 1917-18 | Mr A.Ruffels | 1949-50 | Mr A.J.Law | 1982-83 | Mr Andrew Wheeler 1918-19 | Mr J.Campbell | 1950-51 | Mr P.Venter | 1983-84 | 1919-20 | Mr B.Melman | 1951-52 | Mr P.Venter | 1984-85 | 1920-21 | Mr B.Melman | 1952-53 | Mr Vic Pretorius | 1985-86 | Mr J.Prins 1921-21 | Mr B.Melman | 1953-54 | Mr Vic Pretorius | 1986-87 | 1922-23 | Mr J.Campbell | 1954-55 | | 1987-88 | 1923-24 | | 1954-56 | Mr J.H.A.Roets | 1988-89 | Mr Beyers De Klerk 1924-25 | Mr E.Murton | 1956-57 | Mr P.H.Tredoux | 1989-90 | Mr Gerrie Wolmarans 1925-26 | Mr S.Steenberg | 1957- 58 | | 1990-91 | Mr Gerrie Wolmarans 1926-27 | | 1958-59 | Mr J.M.Cawood | 1991-92 | Mr TJ Ferreira 1927-28 | Mr J.Stanbury | 1959-60 | Mr A.P.Scribante | 1992-93 | Mr Gerrie Wolmarans 1928-29 | Mr E.Murton | 1960-61 | Mr J.L.Viljoen | 1993-94 | Mr TJ Ferreira 1929-30 | Mr K.Turner | 1961-62 | Mr J.L.Viljoen | | 1930-31 | Mr J.E.Bigwood | 1962-63 | Mrs S.Von Wielligh | | 1931-32 | Mr A.Zaretsky | 1963-64 | Mr F.J.Van Heerden | | 1932-33 | Mr G.J.Malan | 1964-65 | | | 1933-34 | | 1965-66 | | | 1934-34 | | 1966-67 | Mr H.McLennan | |
Please identify the row and column numbers of the table displayed in this image. Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_273
WTQ_204-csv_972.jpg
Could you calculate the row number and column number in this table? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Year | Division | League | Regular Season | Playoffs | Open Cup 1998 | 4 | USISL PDSL | 4th, Central | Division Finals | 1st Round 1999 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2000 | 4 | USL PDL | 4th, Rocky Mountain | Did not qualify | Did not qualify 2001 | 4 | USL PDL | 5th, Rocky Mountain | Did not qualify | Did not qualify 2002 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2003 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2004 | 4 | USL PDL | 6th, Heartland | Did not qualify | Did not qualify 2005 | 4 | USL PDL | 3rd, Heartland | Did not qualify | Did not qualify 2006 | 4 | USL PDL | 3rd, Heartland | Did not qualify | Did not qualify 2007 | 4 | USL PDL | 3rd, Heartland | Did not qualify | 1st Round 2008 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2009 | 4 | USL PDL | 6th, Heartland | Did not qualify | Did not qualify 2010 | 4 | USL PDL | 7th, Heartland | Did not qualify | Did not qualify 2011 | 4 | USL PDL | 4th, Heartland | Did not qualify | Did not qualify 2012 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2013 | 4 | USL PDL | 4th, Heartland | Did not qualify | Did not qualify
WTQ_for_TSD
Year | Division | League | Regular Season | Playoffs | Open Cup 1998 | 4 | USISL PDSL | 4th, Central | Division Finals | 1st Round 1999 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2000 | 4 | USL PDL | 4th, Rocky Mountain | Did not qualify | Did not qualify 2001 | 4 | USL PDL | 5th, Rocky Mountain | Did not qualify | Did not qualify 2002 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2003 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2004 | 4 | USL PDL | 6th, Heartland | Did not qualify | Did not qualify 2005 | 4 | USL PDL | 3rd, Heartland | Did not qualify | Did not qualify 2006 | 4 | USL PDL | 3rd, Heartland | Did not qualify | Did not qualify 2007 | 4 | USL PDL | 3rd, Heartland | Did not qualify | 1st Round 2008 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2009 | 4 | USL PDL | 6th, Heartland | Did not qualify | Did not qualify 2010 | 4 | USL PDL | 7th, Heartland | Did not qualify | Did not qualify 2011 | 4 | USL PDL | 4th, Heartland | Did not qualify | Did not qualify 2012 | 4 | USL PDL | 5th, Heartland | Did not qualify | Did not qualify 2013 | 4 | USL PDL | 4th, Heartland | Did not qualify | Did not qualify
Could you calculate the row number and column number in this table? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_274
WTQ_203-csv_53.jpg
Provide me with the row number and column number for the table shown in this image. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Pos | Team | Played | Won | Draw | Lost | Goals For | Goals Against | Goal Difference | Points | Notes 1 | KR | 18 | 11 | 4 | 3 | 27 | 14 | +13 | 37 | UEFA Champions League 2 | Fylkir | 18 | 10 | 5 | 3 | 39 | 16 | +23 | 35 | UEFA Cup 3 | Grindavík | 18 | 8 | 6 | 4 | 25 | 18 | +7 | 30 | UEFA Cup 4 | ÍBV | 18 | 8 | 5 | 5 | 29 | 17 | +12 | 29 | Inter-Toto Cup 5 | ÍA | 18 | 7 | 5 | 6 | 21 | 17 | +4 | 26 | 6 | Keflavík | 18 | 4 | 7 | 7 | 21 | 35 | -14 | 19 | 7 | Breiðablik | 18 | 5 | 3 | 10 | 29 | 35 | -6 | 18 | 8 | Fram | 18 | 4 | 5 | 9 | 22 | 33 | -11 | 17 | 9 | Stjarnan | 18 | 4 | 5 | 9 | 18 | 31 | -13 | 17 | Relegated 10 | Leiftur | 18 | 3 | 7 | 8 | 24 | 39 | -15 | 16 | Relegated
WTQ_for_TSD
Pos | Team | Played | Won | Draw | Lost | Goals For | Goals Against | Goal Difference | Points | Notes 1 | KR | 18 | 11 | 4 | 3 | 27 | 14 | +13 | 37 | UEFA Champions League 2 | Fylkir | 18 | 10 | 5 | 3 | 39 | 16 | +23 | 35 | UEFA Cup 3 | Grindavík | 18 | 8 | 6 | 4 | 25 | 18 | +7 | 30 | UEFA Cup 4 | ÍBV | 18 | 8 | 5 | 5 | 29 | 17 | +12 | 29 | Inter-Toto Cup 5 | ÍA | 18 | 7 | 5 | 6 | 21 | 17 | +4 | 26 | 6 | Keflavík | 18 | 4 | 7 | 7 | 21 | 35 | -14 | 19 | 7 | Breiðablik | 18 | 5 | 3 | 10 | 29 | 35 | -6 | 18 | 8 | Fram | 18 | 4 | 5 | 9 | 22 | 33 | -11 | 17 | 9 | Stjarnan | 18 | 4 | 5 | 9 | 18 | 31 | -13 | 17 | Relegated 10 | Leiftur | 18 | 3 | 7 | 8 | 24 | 39 | -15 | 16 | Relegated
Provide me with the row number and column number for the table shown in this image. Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_275
WTQ_204-csv_189.jpg
Regarding the table displayed, can you identify how many rows and columns it has? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Name | Type | R.A. (J2000) | Dec. (J2000) | Redshift (km/s) | Apparent Magnitude Camelopardalis A | Irr | 04h 26m 16.3s | +72° 48′ 21″ | -46 ± 1 | 14.8 Camelopardalis B | Irr | 04h 53m 07.1s | +67° 05′ 57″ | 77 | 16.1 Cassiopeia 1 | dIrr | 02h 06m 02.8s | +68° 59′ 59″ | 35 | 16.4 IC 342 | SAB(rs)cd | 03h 46m 48.5s | +68° 05′ 46″ | 31 ± 3 | 9.1 KK 35 | Irr | 03h 45m 12.6s | +67° 51′ 51″ | 105 ± 1 | 17.2 NGC 1560 | SA(s)d | 04h 32m 49.1s | +71° 52′ 59″ | -36 ± 5 | 12.2 NGC 1569 | Sbrst | 04h 30m 49.1s | +64° 50′ 52,6″ | -104 ± 4 | 11,2 UGCA 86 | Im | 03h 59m 50.5s | +67° 08′ 37″ | 67 ± 4 | 13.5 UGCA 92 | Im | 04h 32m 04.9s | +63° 36′ 49.0″ | -99 ± 5 | 13.8 UGCA 105 | Im | 05h 14m 15.3s | +62° 34′ 48″ | 111 ± 5 | 13.9
WTQ_for_TSD
Name | Type | R.A. (J2000) | Dec. (J2000) | Redshift (km/s) | Apparent Magnitude Camelopardalis A | Irr | 04h 26m 16.3s | +72° 48′ 21″ | -46 ± 1 | 14.8 Camelopardalis B | Irr | 04h 53m 07.1s | +67° 05′ 57″ | 77 | 16.1 Cassiopeia 1 | dIrr | 02h 06m 02.8s | +68° 59′ 59″ | 35 | 16.4 IC 342 | SAB(rs)cd | 03h 46m 48.5s | +68° 05′ 46″ | 31 ± 3 | 9.1 KK 35 | Irr | 03h 45m 12.6s | +67° 51′ 51″ | 105 ± 1 | 17.2 NGC 1560 | SA(s)d | 04h 32m 49.1s | +71° 52′ 59″ | -36 ± 5 | 12.2 NGC 1569 | Sbrst | 04h 30m 49.1s | +64° 50′ 52,6″ | -104 ± 4 | 11,2 UGCA 86 | Im | 03h 59m 50.5s | +67° 08′ 37″ | 67 ± 4 | 13.5 UGCA 92 | Im | 04h 32m 04.9s | +63° 36′ 49.0″ | -99 ± 5 | 13.8 UGCA 105 | Im | 05h 14m 15.3s | +62° 34′ 48″ | 111 ± 5 | 13.9
Regarding the table displayed, can you identify how many rows and columns it has? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_276
WTQ_200-csv_18.jpg
This image presents a table, and I'd like to know its row and column numbers. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> Frequency | Call sign | Name | Format | Owner | Target city/market | City of license 89.7 FM | KUSD | South Dakota Public Broadcasting | NPR | SD Board of Directors for Educational Telecommunications | Yankton/Vermillion | Vermillion 93.1 FM | KKYA | KK93 | Country | Riverfront Broadcasting LLC | Yankton/Vermillion | Yankton 94.3 FM | KDAM | The Dam | Mainstream Rock | Riverfront Broadcasting LLC | Yankton/Vermillion | Hartington 104.1 FM | WNAX-FM | The Wolf 104.1 | Country | Saga Communications | Yankton/Vermillion | Yankton 106.3 FM | KVHT | Classic Hits 106.3 | Classic Hits | Cullhane Communications, Inc. | Yankton/Vermillion | Vermillion
WTQ_for_TSD
Frequency | Call sign | Name | Format | Owner | Target city/market | City of license 89.7 FM | KUSD | South Dakota Public Broadcasting | NPR | SD Board of Directors for Educational Telecommunications | Yankton/Vermillion | Vermillion 93.1 FM | KKYA | KK93 | Country | Riverfront Broadcasting LLC | Yankton/Vermillion | Yankton 94.3 FM | KDAM | The Dam | Mainstream Rock | Riverfront Broadcasting LLC | Yankton/Vermillion | Hartington 104.1 FM | WNAX-FM | The Wolf 104.1 | Country | Saga Communications | Yankton/Vermillion | Yankton 106.3 FM | KVHT | Classic Hits 106.3 | Classic Hits | Cullhane Communications, Inc. | Yankton/Vermillion | Vermillion
This image presents a table, and I'd like to know its row and column numbers. Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_277
WTQ_203-csv_722.jpg
For the shown table, how many rows and columns are there? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Goal | Date | Venue | Opponent | Score | Result | Competition 1 | 2008-5-28 | Sheriff Stadium, Tiraspol, Moldova | Moldova | 0-1 | 2–2 | Friendly match 2 | 2010-10-12 | Hanrapetakan Stadium, Yerevan, Armenia | Andorra | 4–0 | 4–0 | Euro 2012 Q 3 | 2011-6-4 | Petrovsky Stadium, Saint Petersburg, Russia | Russia | 0-1 | 3–1 | Euro 2012 Q 4 | 2011-9-2 | Estadi Comunal d'Aixovall, Andorra la Vella, Andorra | Andorra | 0-1 | 0-3 | Euro 2012 Q 5 | 2011-10-7 | Hanrapetakan Stadium, Yerevan, Armenia | Macedonia | 1-0 | 4-1 | Euro 2012 Q 6 | 2012-2-29 | Tsirion Stadium, Limassol, Cyprus | Canada | 1-1 | 1-3 | Friendly match 7 | 2012-2-29 | Tsirion Stadium, Limassol, Cyprus | Canada | 1-2 | 1-3 | Friendly match
WTQ_for_TSD
Goal | Date | Venue | Opponent | Score | Result | Competition 1 | 2008-5-28 | Sheriff Stadium, Tiraspol, Moldova | Moldova | 0-1 | 2–2 | Friendly match 2 | 2010-10-12 | Hanrapetakan Stadium, Yerevan, Armenia | Andorra | 4–0 | 4–0 | Euro 2012 Q 3 | 2011-6-4 | Petrovsky Stadium, Saint Petersburg, Russia | Russia | 0-1 | 3–1 | Euro 2012 Q 4 | 2011-9-2 | Estadi Comunal d'Aixovall, Andorra la Vella, Andorra | Andorra | 0-1 | 0-3 | Euro 2012 Q 5 | 2011-10-7 | Hanrapetakan Stadium, Yerevan, Armenia | Macedonia | 1-0 | 4-1 | Euro 2012 Q 6 | 2012-2-29 | Tsirion Stadium, Limassol, Cyprus | Canada | 1-1 | 1-3 | Friendly match 7 | 2012-2-29 | Tsirion Stadium, Limassol, Cyprus | Canada | 1-2 | 1-3 | Friendly match
For the shown table, how many rows and columns are there? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_278
WTQ_203-csv_733.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Rank | Cyclist | Team | Time | UCI ProTour Points 1 | Alejandro Valverde (ESP) | Caisse d'Epargne | 5h 29' 10\",40" 2 | Alexandr Kolobnev (RUS) | Team CSC Saxo Bank | s.t. | 30 3 | Davide Rebellin (ITA) | Gerolsteiner | s.t. | 25 4 | Paolo Bettini (ITA) | Quick Step | s.t. | 20 5 | Franco Pellizotti (ITA) | Liquigas | s.t. | 15 6 | Denis Menchov (RUS) | Rabobank | s.t. | 11 7 | Samuel Sánchez (ESP) | Euskaltel-Euskadi | s.t. | 7 8 | Stéphane Goubert (FRA) | Ag2r-La Mondiale | + 2\",5" 9 | Haimar Zubeldia (ESP) | Euskaltel-Euskadi | + 2\",3" 10 | David Moncoutié (FRA) | Cofidis | + 2\",1"
WTQ_for_TSD
Rank | Cyclist | Team | Time | UCI ProTour Points 1 | Alejandro Valverde (ESP) | Caisse d'Epargne | 5h 29' 10\",40" 2 | Alexandr Kolobnev (RUS) | Team CSC Saxo Bank | s.t. | 30 3 | Davide Rebellin (ITA) | Gerolsteiner | s.t. | 25 4 | Paolo Bettini (ITA) | Quick Step | s.t. | 20 5 | Franco Pellizotti (ITA) | Liquigas | s.t. | 15 6 | Denis Menchov (RUS) | Rabobank | s.t. | 11 7 | Samuel Sánchez (ESP) | Euskaltel-Euskadi | s.t. | 7 8 | Stéphane Goubert (FRA) | Ag2r-La Mondiale | + 2\",5" 9 | Haimar Zubeldia (ESP) | Euskaltel-Euskadi | + 2\",3" 10 | David Moncoutié (FRA) | Cofidis | + 2\",1"
For the table shown in this image, can you tell me the row and column numbers of this table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_279
WTQ_204-csv_591.jpg
Could you count the number of rows and columns in this table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Week | Date | Opponent | Result | Attendance 1 | September 4, 1988 | at Detroit Lions | L 31–17 | 31,075 2 | September 11, 1988 | New Orleans Saints | L 29–21 | 48,901 3 | September 18, 1988 | at San Francisco 49ers | W 34–17 | 60,168 4 | September 25, 1988 | at Dallas Cowboys | L 26–20 | 39,702 5 | October 2, 1988 | Seattle Seahawks | L 31–20 | 28,619 6 | October 9, 1988 | Los Angeles Rams | L 33–0 | 30,852 7 | October 16, 1988 | at Denver Broncos | L 30–14 | 75,287 8 | October 23, 1988 | New York Giants | L 23–16 | 45,092 9 | October 30, 1988 | at Philadelphia Eagles | W 27–24 | 60,091 10 | November 6, 1988 | Green Bay Packers | W 20–0 | 29,952 11 | November 13, 1988 | San Diego Chargers | L 10–7 | 26,329 12 | November 20, 1988 | at Los Angeles Raiders | W 12–6 | 40,967 13 | November 27, 1988 | Tampa Bay Buccaneers | W 17–10 | 14,020 14 | December 4, 1988 | San Francisco 49ers | L 13–3 | 44,048 15 | December 11, 1988 | at Los Angeles Rams | L 22–7 | 42,828 16 | December 18, 1988 | at New Orleans Saints | L 10–9 | 60,566
WTQ_for_TSD
Week | Date | Opponent | Result | Attendance 1 | September 4, 1988 | at Detroit Lions | L 31–17 | 31,075 2 | September 11, 1988 | New Orleans Saints | L 29–21 | 48,901 3 | September 18, 1988 | at San Francisco 49ers | W 34–17 | 60,168 4 | September 25, 1988 | at Dallas Cowboys | L 26–20 | 39,702 5 | October 2, 1988 | Seattle Seahawks | L 31–20 | 28,619 6 | October 9, 1988 | Los Angeles Rams | L 33–0 | 30,852 7 | October 16, 1988 | at Denver Broncos | L 30–14 | 75,287 8 | October 23, 1988 | New York Giants | L 23–16 | 45,092 9 | October 30, 1988 | at Philadelphia Eagles | W 27–24 | 60,091 10 | November 6, 1988 | Green Bay Packers | W 20–0 | 29,952 11 | November 13, 1988 | San Diego Chargers | L 10–7 | 26,329 12 | November 20, 1988 | at Los Angeles Raiders | W 12–6 | 40,967 13 | November 27, 1988 | Tampa Bay Buccaneers | W 17–10 | 14,020 14 | December 4, 1988 | San Francisco 49ers | L 13–3 | 44,048 15 | December 11, 1988 | at Los Angeles Rams | L 22–7 | 42,828 16 | December 18, 1988 | at New Orleans Saints | L 10–9 | 60,566
Could you count the number of rows and columns in this table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_280
WTQ_203-csv_819.jpg
Could you count the number of rows and columns in this table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Year | Competition | Venue | Position | Notes 1999 | World Youth Championships | Bydgoszcz, Poland | 12th | 2000 | World Junior Championships | Santiago, Chile | 5th | 2001 | European Junior Championships | Grosseto, Italy | 2nd | 61.97 m 2001 | World Championships | Edmonton, Canada | 23rd | 61.26 m 2002 | World Junior Championships | Kingston, Jamaica | 2nd | 63.91 m 2002 | European Championships | Munich, Germany | 26th | 60.28 m 2006 | European Championships | Gothenburg, Sweden | 26th | 62.39 m 2007 | World Student Games | Bangkok, Thailand | 5th | 64.95 m 2007 | World Championships | Osaka, Japan | 13th | 68.15 m 2008 | Olympic Games | Beijing, PR China | 8th | 71.00 m 2008 | World Athletics Final | Stuttgart, Germany | 2nd | 71.40 m 2009 | World Student Games | Belgrade, Serbia | 2nd | 72.85 m 2009 | World Championships | Berlin, Germany | 3rd | 74.79 m 2009 | World Athletics Final | Thessaloniki, Greece | 3rd | 70.45 m 2012 | European Championships | Helsinki, Finland | 2nd | 73.34 m
WTQ_for_TSD
Year | Competition | Venue | Position | Notes 1999 | World Youth Championships | Bydgoszcz, Poland | 12th | 2000 | World Junior Championships | Santiago, Chile | 5th | 2001 | European Junior Championships | Grosseto, Italy | 2nd | 61.97 m 2001 | World Championships | Edmonton, Canada | 23rd | 61.26 m 2002 | World Junior Championships | Kingston, Jamaica | 2nd | 63.91 m 2002 | European Championships | Munich, Germany | 26th | 60.28 m 2006 | European Championships | Gothenburg, Sweden | 26th | 62.39 m 2007 | World Student Games | Bangkok, Thailand | 5th | 64.95 m 2007 | World Championships | Osaka, Japan | 13th | 68.15 m 2008 | Olympic Games | Beijing, PR China | 8th | 71.00 m 2008 | World Athletics Final | Stuttgart, Germany | 2nd | 71.40 m 2009 | World Student Games | Belgrade, Serbia | 2nd | 72.85 m 2009 | World Championships | Berlin, Germany | 3rd | 74.79 m 2009 | World Athletics Final | Thessaloniki, Greece | 3rd | 70.45 m 2012 | European Championships | Helsinki, Finland | 2nd | 73.34 m
Could you count the number of rows and columns in this table? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_281
WTQ_203-csv_87.jpg
Please identify the row and column numbers of the table displayed in this image. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Subject | Robot's Name | Who? | When? | Where? | Occupation Solar System | Cosmo-Bot | Copernicus | 1531 | Poland | Cosmonaut Olympics | Rhonda Robot | Greeks | 776 B.C. | Greece | Beauty queen Basketball | Danny Defrost-Bot | James Naismith | 1891 | United States | Snowman Nursing | Dr. Bug-Bot | Florence Nightengale | 1860 | England | Doctor Scuba Gear | Flip the High-Diving Robot | Jacques Cousteau | 1946 | France | Diver Helicopter | Amelia Air-Bot | Leonardo da Vinci | 1483 | Italy | Pilot Corn Flakes | Chef Boy-Robot | William Kellogg | 1894 | Battle Creek, Michigan | Cook Radium | Miss Battery-Bot | Marie Curie | 1898 | France | Battery Lady Chewing Gum | Bubble-Bot | Mayans | 400 | Mexico | Bubble Man Painting | Pierro-Bot | Stone-Age Humans | 35,000 B.C. | Europe | Clown/Artist Phonograph | Slide the Heavy-Metal Robot | Thomas Edison | 1877 | New Jersey | Rock Star Paper | Noshi Origami | Ts'ai Lun | 105 | China | Origami Maker Round Earth | Vasco da Robot | Ferdinand Magellan | 1522 | Spain | Early Sailor Dynamite | Robby Robot | Alfred Nobel | 1866 | Sweden | Prankster Microscope | Slobot | Antonie van Leeuwenhoek | 1674 | The Netherlands | Dirty Person Writing | Eraser-Bot | Sumerians | 3,500 B.C. | Middle East | Pencil Man Sausage | Sock-Bot | Babylonians | 3,000 B.C. | Middle East | Sock Man Bicycle | Booster-Bot | Karl von Drais | 1816 | Germany | Rocket Man Wheel | Rollin' Road-Bot | Sumerians | 3,000 B.C. | Middle East | Race Starter Germs | Roast-Bot | Louis Pasteur | 1865 | France | Firefighter Boomerang | Oswald the Mailman Robot | Aborigines | 40,000 years ago | Australia | Mailman Coins | Verna the Vend-Bot | Lydians | 600 B.C. | Turkey | Vending Machine Tools | Hank the Handyman Robot | Stone-Age Humans | 2½ million years ago | Africa | Mechanic Saxophone | Bongo-Bot the Six-Armed Robot | Antoine-Joseph Sax | 1846 | France | Six-Armed Drum Player Toilet | Brunwella the Bombshell | Minoans | 2000 B.C. | Crete | Demolisher
WTQ_for_TSD
Subject | Robot's Name | Who? | When? | Where? | Occupation Solar System | Cosmo-Bot | Copernicus | 1531 | Poland | Cosmonaut Olympics | Rhonda Robot | Greeks | 776 B.C. | Greece | Beauty queen Basketball | Danny Defrost-Bot | James Naismith | 1891 | United States | Snowman Nursing | Dr. Bug-Bot | Florence Nightengale | 1860 | England | Doctor Scuba Gear | Flip the High-Diving Robot | Jacques Cousteau | 1946 | France | Diver Helicopter | Amelia Air-Bot | Leonardo da Vinci | 1483 | Italy | Pilot Corn Flakes | Chef Boy-Robot | William Kellogg | 1894 | Battle Creek, Michigan | Cook Radium | Miss Battery-Bot | Marie Curie | 1898 | France | Battery Lady Chewing Gum | Bubble-Bot | Mayans | 400 | Mexico | Bubble Man Painting | Pierro-Bot | Stone-Age Humans | 35,000 B.C. | Europe | Clown/Artist Phonograph | Slide the Heavy-Metal Robot | Thomas Edison | 1877 | New Jersey | Rock Star Paper | Noshi Origami | Ts'ai Lun | 105 | China | Origami Maker Round Earth | Vasco da Robot | Ferdinand Magellan | 1522 | Spain | Early Sailor Dynamite | Robby Robot | Alfred Nobel | 1866 | Sweden | Prankster Microscope | Slobot | Antonie van Leeuwenhoek | 1674 | The Netherlands | Dirty Person Writing | Eraser-Bot | Sumerians | 3,500 B.C. | Middle East | Pencil Man Sausage | Sock-Bot | Babylonians | 3,000 B.C. | Middle East | Sock Man Bicycle | Booster-Bot | Karl von Drais | 1816 | Germany | Rocket Man Wheel | Rollin' Road-Bot | Sumerians | 3,000 B.C. | Middle East | Race Starter Germs | Roast-Bot | Louis Pasteur | 1865 | France | Firefighter Boomerang | Oswald the Mailman Robot | Aborigines | 40,000 years ago | Australia | Mailman Coins | Verna the Vend-Bot | Lydians | 600 B.C. | Turkey | Vending Machine Tools | Hank the Handyman Robot | Stone-Age Humans | 2½ million years ago | Africa | Mechanic Saxophone | Bongo-Bot the Six-Armed Robot | Antoine-Joseph Sax | 1846 | France | Six-Armed Drum Player Toilet | Brunwella the Bombshell | Minoans | 2000 B.C. | Crete | Demolisher
Please identify the row and column numbers of the table displayed in this image. Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_282
WTQ_203-csv_575.jpg
For the shown table, how many rows and columns are there? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Iteration | Dates | Location | Attendance | Notes GameStorm 10 | March 2008 | Red Lion - Vancouver, WA | 750 | - GameStorm 11 | March 26–29, 2009 | Hilton - Vancouver, WA | 736 | debut of Video games, first-ever Artist Guest of Honor, Rob Alexander GameStorm 12 | March 25–28, 2010 | Hilton - Vancouver, WA | 802 | Board games Guest of Honor: Tom Lehmann GameStorm 13 | March 24–27, 2011 | Hilton - Vancouver, WA | 984 | Guests: Lisa Steenson, Michael A. Stackpole GameStorm 14 | March 22–25, 2012 | Hilton - Vancouver, WA | 1072 | Boardgame:Andrew Hackard and Sam Mitschke of Steve Jackson Games - RPG: Jason Bulmahn GameStorm 15 | March 21–24, 2013 | Hilton - Vancouver, WA | 1188 | GameStorm 16 | March 20–23, 2014 | Hilton - Vancouver, WA | tba | Guests: Mike Selinker, Shane Lacy Hensley, Lisa Steenson, Zev Shlasinger of Z-Man Games
WTQ_for_TSD
Iteration | Dates | Location | Attendance | Notes GameStorm 10 | March 2008 | Red Lion - Vancouver, WA | 750 | - GameStorm 11 | March 26–29, 2009 | Hilton - Vancouver, WA | 736 | debut of Video games, first-ever Artist Guest of Honor, Rob Alexander GameStorm 12 | March 25–28, 2010 | Hilton - Vancouver, WA | 802 | Board games Guest of Honor: Tom Lehmann GameStorm 13 | March 24–27, 2011 | Hilton - Vancouver, WA | 984 | Guests: Lisa Steenson, Michael A. Stackpole GameStorm 14 | March 22–25, 2012 | Hilton - Vancouver, WA | 1072 | Boardgame:Andrew Hackard and Sam Mitschke of Steve Jackson Games - RPG: Jason Bulmahn GameStorm 15 | March 21–24, 2013 | Hilton - Vancouver, WA | 1188 | GameStorm 16 | March 20–23, 2014 | Hilton - Vancouver, WA | tba | Guests: Mike Selinker, Shane Lacy Hensley, Lisa Steenson, Zev Shlasinger of Z-Man Games
For the shown table, how many rows and columns are there? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_283
WTQ_204-csv_720.jpg
Could you calculate the row number and column number in this table? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> Number | Name | Term Started | Term Ended | Alma Mater | Field(s) | Educational Background 1 | Dr Abdus Salam | 1961 | 1967 | Imperial College | Theoretical Physics | Doctor of Philosophy (Ph.D) 2 | Air Commodore Dr Władysław Turowicz | 1967 | 1979 | Warsaw University of Technology | Aeronautical Engineering | Ph.D 3 | Air Commodore K. M. Ahmad | 1979 | 1980 | Pakistan Air Force Academy | Flight Instructor | Certificated Flight Instructor (CFI) 4 | Dr Salim Mehmud | 1980 | 1989 | Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory | Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering | Ph.D 5 | Dr M. Shafi Ahmad | 1989 | 1990 | University of London | Astronomy | Ph.D 6 | Engr.Sikandar Zaman | 1990 | 1997 | University of Leeds | Mechanical Engineering | Bachelor of Science (B.S.) 7 | Dr Abdul Majid | 1997 | 2001 | University of Wales | Astrophysics | Ph.D 8 | Major General Raza Hussain | 2001 | 2010 | Pakistan Army Corps of Electrical and Mechanical Engineers | Electrical Engineering | B.S. 9 | Major General Ahmed Bilal | 2010 | Present | Pakistan Army Corps of Signals Engineering | Computer Engineering | Master of Science (M.S)
WTQ_for_TSD
Number | Name | Term Started | Term Ended | Alma Mater | Field(s) | Educational Background 1 | Dr Abdus Salam | 1961 | 1967 | Imperial College | Theoretical Physics | Doctor of Philosophy (Ph.D) 2 | Air Commodore Dr Władysław Turowicz | 1967 | 1979 | Warsaw University of Technology | Aeronautical Engineering | Ph.D 3 | Air Commodore K. M. Ahmad | 1979 | 1980 | Pakistan Air Force Academy | Flight Instructor | Certificated Flight Instructor (CFI) 4 | Dr Salim Mehmud | 1980 | 1989 | Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory | Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering | Ph.D 5 | Dr M. Shafi Ahmad | 1989 | 1990 | University of London | Astronomy | Ph.D 6 | Engr.Sikandar Zaman | 1990 | 1997 | University of Leeds | Mechanical Engineering | Bachelor of Science (B.S.) 7 | Dr Abdul Majid | 1997 | 2001 | University of Wales | Astrophysics | Ph.D 8 | Major General Raza Hussain | 2001 | 2010 | Pakistan Army Corps of Electrical and Mechanical Engineers | Electrical Engineering | B.S. 9 | Major General Ahmed Bilal | 2010 | Present | Pakistan Army Corps of Signals Engineering | Computer Engineering | Master of Science (M.S)
Could you calculate the row number and column number in this table? Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_284
WTQ_204-csv_410.jpg
For the shown table, how many rows and columns are there? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> # | Player | Goals | Caps | Career 1 | Landon Donovan | 57 | 155 | 2000–present 2 | Clint Dempsey | 36 | 103 | 2004–present 3 | Eric Wynalda | 34 | 106 | 1990–2000 4 | Brian McBride | 30 | 95 | 1993–2006 5 | Joe-Max Moore | 24 | 100 | 1992–2002 6T | Jozy Altidore | 21 | 67 | 2007–present 6T | Bruce Murray | 21 | 86 | 1985–1993 8 | Eddie Johnson | 19 | 62 | 2004–present 9T | Earnie Stewart | 17 | 101 | 1990–2004 9T | DaMarcus Beasley | 17 | 114 | 2001–present
WTQ_for_TSD
# | Player | Goals | Caps | Career 1 | Landon Donovan | 57 | 155 | 2000–present 2 | Clint Dempsey | 36 | 103 | 2004–present 3 | Eric Wynalda | 34 | 106 | 1990–2000 4 | Brian McBride | 30 | 95 | 1993–2006 5 | Joe-Max Moore | 24 | 100 | 1992–2002 6T | Jozy Altidore | 21 | 67 | 2007–present 6T | Bruce Murray | 21 | 86 | 1985–1993 8 | Eddie Johnson | 19 | 62 | 2004–present 9T | Earnie Stewart | 17 | 101 | 1990–2004 9T | DaMarcus Beasley | 17 | 114 | 2001–present
For the shown table, how many rows and columns are there? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_285
WTQ_203-csv_628.jpg
This image displays a table. Could you provide me with the row number and column number corresponding to this table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> Year | Song | US Hot 100 | U.S. Modern Rock | U.S. Mainstream Rock | Album 1997 | \Pacifier\"" | - | - | - | Pacifier 1997 | \One Thing\"" | - | - | - | Pacifier 1997 | \Defaced\"" | - | - | - | Pacifier 1998 | \Breathe Out\"" | - | - | - | An Audio Guide To Everyday Atrocity 1998 | \The Sick\"" | - | - | - | An Audio Guide To Everyday Atrocity 2001 | \Bleeder\"" | - | - | 32 | Violence 2003 | \Ether\"" | - | - | - | Skeletons
WTQ_for_TSD
Year | Song | US Hot 100 | U.S. Modern Rock | U.S. Mainstream Rock | Album 1997 | \Pacifier\"" | - | - | - | Pacifier 1997 | \One Thing\"" | - | - | - | Pacifier 1997 | \Defaced\"" | - | - | - | Pacifier 1998 | \Breathe Out\"" | - | - | - | An Audio Guide To Everyday Atrocity 1998 | \The Sick\"" | - | - | - | An Audio Guide To Everyday Atrocity 2001 | \Bleeder\"" | - | - | 32 | Violence 2003 | \Ether\"" | - | - | - | Skeletons
This image displays a table. Could you provide me with the row number and column number corresponding to this table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_286
WTQ_203-csv_373.jpg
What is the count of rows and columns in the given table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}. <TAB> Rank | Diver | Preliminary Points | Preliminary Rank | Final Points | Sylvie Bernier (CAN) | 489.51 | 3 | 530.70 | Kelly McCormick (USA) | 516.75 | 2 | 527.46 | Christina Seufert (USA) | 481.41 | 5 | 517.62 4 | Li Yihua (CHN) | 517.92 | 1 | 506.52 5 | Li Qiaoxian (CHN) | 466.83 | 6 | 487.68 6 | Elsa Tenorio (MEX) | 460.56 | 8 | 463.56 7 | Lesley Smith (ZIM) | 438.72 | 10 | 451.89 8 | Debbie Fuller (CAN) | 437.04 | 11 | 450.99 9 | Jennifer Donnet (AUS) | 432.78 | 12 | 443.13 10 | Daphne Jongejans (NED) | 487.95 | 4 | 437.40 11 | Anita Rossing (SWE) | 464.58 | 7 | 424.98 12 | Verónica Ribot (ARG) | 443.25 | 9 | 422.52 13 | Ann Fargher (NZL) | 421.65 | 13 | 14 | Tine Tollan (NOR) | 419.55 | 14 | 15 | Antonette Wilken (ZIM) | 414.66 | 15 | 16 | Guadalupe Canseco (MEX) | 411.96 | 16 | 17 | Claire Izacard (FRA) | 403.17 | 17 | 18 | Valerie McFarland-Beddoe (AUS) | 401.13 | 18 | 19 | Alison Childs (GBR) | 400.68 | 19 | 20 | Kerstin Finke (FRG) | 393.93 | 20 | 21 | Nicole Kreil (AUT) | 382.68 | 21 | 22 | Joana Figueiredo (POR) | 374.07 | 22 | 23 | Angela Ribeiro (BRA) | 370.68 | 23 | 24 | Rim Hassan (EGY) | 258.63 | 24 |
WTQ_for_TSD
Rank | Diver | Preliminary Points | Preliminary Rank | Final Points | Sylvie Bernier (CAN) | 489.51 | 3 | 530.70 | Kelly McCormick (USA) | 516.75 | 2 | 527.46 | Christina Seufert (USA) | 481.41 | 5 | 517.62 4 | Li Yihua (CHN) | 517.92 | 1 | 506.52 5 | Li Qiaoxian (CHN) | 466.83 | 6 | 487.68 6 | Elsa Tenorio (MEX) | 460.56 | 8 | 463.56 7 | Lesley Smith (ZIM) | 438.72 | 10 | 451.89 8 | Debbie Fuller (CAN) | 437.04 | 11 | 450.99 9 | Jennifer Donnet (AUS) | 432.78 | 12 | 443.13 10 | Daphne Jongejans (NED) | 487.95 | 4 | 437.40 11 | Anita Rossing (SWE) | 464.58 | 7 | 424.98 12 | Verónica Ribot (ARG) | 443.25 | 9 | 422.52 13 | Ann Fargher (NZL) | 421.65 | 13 | 14 | Tine Tollan (NOR) | 419.55 | 14 | 15 | Antonette Wilken (ZIM) | 414.66 | 15 | 16 | Guadalupe Canseco (MEX) | 411.96 | 16 | 17 | Claire Izacard (FRA) | 403.17 | 17 | 18 | Valerie McFarland-Beddoe (AUS) | 401.13 | 18 | 19 | Alison Childs (GBR) | 400.68 | 19 | 20 | Kerstin Finke (FRG) | 393.93 | 20 | 21 | Nicole Kreil (AUT) | 382.68 | 21 | 22 | Joana Figueiredo (POR) | 374.07 | 22 | 23 | Angela Ribeiro (BRA) | 370.68 | 23 | 24 | Rim Hassan (EGY) | 258.63 | 24 |
What is the count of rows and columns in the given table? The final result should be presented in the JSON format of {"row_number": "m", "column_number": "n"}.
TSD_test_item_287
WTQ_204-csv_182.jpg
Could you count the number of rows and columns in this table? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> May 20-21 118 | March 9 120 | December 25-26 122 | October 13-14 124 | August 1-2 126 May 21, 1993 | March 9, 1997 | December 25, 2000 | October 14, 2004 | August 1, 2008 128 | 130 | 132 | 134 | 136 May 20, 2012 | March 9, 2016 | December 26, 2019 | October 14, 2023 | August 2, 2027 138 | 140 | 142 | 144 | 146 May 21, 2031 | March 9, 2035 | December 26, 2038 | October 14, 2042 | August 2, 2046 148 | 150 | 152 | 154 | 156 May 20, 2050 | March 9, 2054 | December 26, 2057 | October 13, 2061 | August 2, 2065
WTQ_for_TSD
May 20-21 118 | March 9 120 | December 25-26 122 | October 13-14 124 | August 1-2 126 May 21, 1993 | March 9, 1997 | December 25, 2000 | October 14, 2004 | August 1, 2008 128 | 130 | 132 | 134 | 136 May 20, 2012 | March 9, 2016 | December 26, 2019 | October 14, 2023 | August 2, 2027 138 | 140 | 142 | 144 | 146 May 21, 2031 | March 9, 2035 | December 26, 2038 | October 14, 2042 | August 2, 2046 148 | 150 | 152 | 154 | 156 May 20, 2050 | March 9, 2054 | December 26, 2057 | October 13, 2061 | August 2, 2065
Could you count the number of rows and columns in this table? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_288
WTQ_203-csv_334.jpg
Regarding the table displayed, can you identify how many rows and columns it has? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}. <TAB> Week | Date | Opponent | Result | Game site | NFL Recap | Attendance 1 | September 8, 1986 | New York Giants | W 31–28 | Texas Stadium | [1] | 59,804 2 | September 14, 1986 | at Detroit Lions | W 31–7 | Pontiac Silverdome | [2] | 73,812 3 | September 21, 1986 | Atlanta Falcons | L 35–37 | Texas Stadium | [3] | 62,880 4 | September 29, 1986 | at St. Louis Cardinals | W 31–7 | Busch Memorial Stadium | [4] | 49,077 5 | October 5, 1986 | at Denver Broncos | L 14–29 | Mile High Stadium | [5] | 76,082 6 | October 12, 1986 | Washington Redskins | W 30–6 | Texas Stadium | [6] | 63,264 7 | October 19, 1986 | at Philadelphia Eagles | W 17–14 | Veterans Stadium | [7] | 68,572 8 | October 26, 1986 | St. Louis Cardinals | W 37–6 | Texas Stadium | [8] | 60,756 9 | November 2, 1986 | at New York Giants | L 14–17 | Giants Stadium | [9] | 74,871 10 | November 9, 1986 | Los Angeles Raiders | L 13–17 | Texas Stadium | [10] | 61,706 11 | November 16, 1986 | at San Diego Chargers | W 24–21 | Jack Murphy Stadium | [11] | 55,622 12 | November 23, 1986 | at Washington Redskins | L 14–41 | RFK Stadium | [12] | 55,642 13 | November 27, 1986 | Seattle Seahawks | L 14–31 | Texas Stadium | [13] | 58,020 14 | December 7, 1986 | at Los Angeles Rams | L 10–29 | Anaheim Stadium | [14] | 64,949 15 | December 14, 1986 | Philadelphia Eagles | L 21–23 | Texas Stadium | [15] | 46,117 16 | December 21, 1986 | Chicago Bears | L 10–24 | Texas Stadium | [16] | 57,256
WTQ_for_TSD
Week | Date | Opponent | Result | Game site | NFL Recap | Attendance 1 | September 8, 1986 | New York Giants | W 31–28 | Texas Stadium | [1] | 59,804 2 | September 14, 1986 | at Detroit Lions | W 31–7 | Pontiac Silverdome | [2] | 73,812 3 | September 21, 1986 | Atlanta Falcons | L 35–37 | Texas Stadium | [3] | 62,880 4 | September 29, 1986 | at St. Louis Cardinals | W 31–7 | Busch Memorial Stadium | [4] | 49,077 5 | October 5, 1986 | at Denver Broncos | L 14–29 | Mile High Stadium | [5] | 76,082 6 | October 12, 1986 | Washington Redskins | W 30–6 | Texas Stadium | [6] | 63,264 7 | October 19, 1986 | at Philadelphia Eagles | W 17–14 | Veterans Stadium | [7] | 68,572 8 | October 26, 1986 | St. Louis Cardinals | W 37–6 | Texas Stadium | [8] | 60,756 9 | November 2, 1986 | at New York Giants | L 14–17 | Giants Stadium | [9] | 74,871 10 | November 9, 1986 | Los Angeles Raiders | L 13–17 | Texas Stadium | [10] | 61,706 11 | November 16, 1986 | at San Diego Chargers | W 24–21 | Jack Murphy Stadium | [11] | 55,622 12 | November 23, 1986 | at Washington Redskins | L 14–41 | RFK Stadium | [12] | 55,642 13 | November 27, 1986 | Seattle Seahawks | L 14–31 | Texas Stadium | [13] | 58,020 14 | December 7, 1986 | at Los Angeles Rams | L 10–29 | Anaheim Stadium | [14] | 64,949 15 | December 14, 1986 | Philadelphia Eagles | L 21–23 | Texas Stadium | [15] | 46,117 16 | December 21, 1986 | Chicago Bears | L 10–24 | Texas Stadium | [16] | 57,256
Regarding the table displayed, can you identify how many rows and columns it has? Format your final answer as a JSON, using the structure {"row_number": "m", "column_number": "n"}.
TSD_test_item_289
WTQ_203-csv_402.jpg
I'd like to know the total number of rows and columns in the provided table. Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> Date | Festival | Location | Awards | Link Feb 2–5, Feb 11 | Santa Barbara International Film Festival | Santa Barbara, California USA | Top 11 \Best of the Fest\" Selection" | sbiff.org May 21–22, Jun 11 | Seattle International Film Festival | Seattle, Washington USA | | siff.net Jul 18, Jul 25 | Fantasia Festival | Montreal, Quebec Canada | Special Mention \for the resourcefulness and unwavering determination by a director to realize his unique vision\"" | FanTasia Sep 16 | Athens International Film Festival | Athens, Attica Greece | Best Director | aiff.gr Sep 19 | Lund International Fantastic Film Festival | Lund, Skåne Sweden | | fff.se Sep 28 | Fantastic Fest | Austin, Texas USA | | FantasticFest.com Oct 9 | London Int. Festival of Science Fiction Film | London, England UK | Closing Night Film | Sci-Fi London Oct 9, Oct 11 | Sitges Film Festival | Sitges, Catalonia Spain | | Sitges Festival Oct 1, Oct 15 | Gwacheon International SF Festival | Gwacheon, Gyeonggi-do South Korea | | gisf.org Oct 17, Oct 20 | Icon TLV | Tel Aviv, Central Israel | | icon.org.il Oct 23 | Toronto After Dark | Toronto, Ontario Canada | Best Special Effects Best Musical Score | torontoafterdark.com Nov 11 | Les Utopiales | Nantes, Pays de la Loire France | | utopiales.org Nov 12, Nov 18 | Indonesia Fantastic Film Festival | Jakarta, Bandung Indonesia | | inaff.com Nov 16–18 | AFF | Wrocław, Lower Silesia Poland | | AFF Poland
WTQ_for_TSD
Date | Festival | Location | Awards | Link Feb 2–5, Feb 11 | Santa Barbara International Film Festival | Santa Barbara, California USA | Top 11 \Best of the Fest\" Selection" | sbiff.org May 21–22, Jun 11 | Seattle International Film Festival | Seattle, Washington USA | | siff.net Jul 18, Jul 25 | Fantasia Festival | Montreal, Quebec Canada | Special Mention \for the resourcefulness and unwavering determination by a director to realize his unique vision\"" | FanTasia Sep 16 | Athens International Film Festival | Athens, Attica Greece | Best Director | aiff.gr Sep 19 | Lund International Fantastic Film Festival | Lund, Skåne Sweden | | fff.se Sep 28 | Fantastic Fest | Austin, Texas USA | | FantasticFest.com Oct 9 | London Int. Festival of Science Fiction Film | London, England UK | Closing Night Film | Sci-Fi London Oct 9, Oct 11 | Sitges Film Festival | Sitges, Catalonia Spain | | Sitges Festival Oct 1, Oct 15 | Gwacheon International SF Festival | Gwacheon, Gyeonggi-do South Korea | | gisf.org Oct 17, Oct 20 | Icon TLV | Tel Aviv, Central Israel | | icon.org.il Oct 23 | Toronto After Dark | Toronto, Ontario Canada | Best Special Effects Best Musical Score | torontoafterdark.com Nov 11 | Les Utopiales | Nantes, Pays de la Loire France | | utopiales.org Nov 12, Nov 18 | Indonesia Fantastic Film Festival | Jakarta, Bandung Indonesia | | inaff.com Nov 16–18 | AFF | Wrocław, Lower Silesia Poland | | AFF Poland
I'd like to know the total number of rows and columns in the provided table. Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_290
WTQ_204-csv_995.jpg
This image displays a table. Could you provide me with the row number and column number corresponding to this table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Year | Class | No | Tyres | Car | Team | Co-Drivers | Laps | Pos. | Class Pos. 1972 | S 3.0 | 22 | | Ligier JS2 Maserati 3.0L V6 | Automobiles Ligier | Pierre Maublanc | 195 | DNF | DNF 1973 | S 3.0 | 62 | | Ligier JS2 Maserati 3.0L V6 | Automobiles Ligier | Guy Ligier | 24 | DSQ | DSQ 1974 | S 3.0 | 15 | | Ligier JS2 Maserati 3.0L V6 | Automobiles Ligier | Alain Serpaggi | 310 | 8th | 5th 1977 | S +2.0 | 8 | | Renault Alpine A442 Renault 2.0L Turbo V6 | Renault Sport | Patrick Depailler | 289 | DNF | DNF 1978 | S +2.0 | 10 | | Mirage M9 Renault 2.0L Turbo V6 | Grand Touring Cars Inc. | Vern Schuppan Sam Posey | 293 | 10th | 5th 1990 | C1 | 6 | G | Porsche 962C Porsche Type-935 3.0L Turbo Flat-6 | Joest Porsche Racing | Henri Pescarolo Jean-Louis Ricci | 328 | 14th | 14th 1993 | GT | 71 | D | Venturi 500LM Renault PRV 3.0 L Turbo V6 | Jacadi Racing | Michel Maisonneuve Christophe Dechavanne | 210 | DNF | DNF 1994 | GT2 | 49 | P | Porsche 911 Carrera RSR Porsche 3.8 L Flat-6 | Larbre Compétition | Jacques Alméras Jean-Marie Alméras | 94 | DNF | DNF 1996 | GT1 | 38 | M | McLaren F1 GTR BMW S70 6.1L V12 | Team Bigazzi SRL | Steve Soper Marc Duez | 318 | 11th | 9th
WTQ_for_TSD
Year | Class | No | Tyres | Car | Team | Co-Drivers | Laps | Pos. | Class Pos. 1972 | S 3.0 | 22 | | Ligier JS2 Maserati 3.0L V6 | Automobiles Ligier | Pierre Maublanc | 195 | DNF | DNF 1973 | S 3.0 | 62 | | Ligier JS2 Maserati 3.0L V6 | Automobiles Ligier | Guy Ligier | 24 | DSQ | DSQ 1974 | S 3.0 | 15 | | Ligier JS2 Maserati 3.0L V6 | Automobiles Ligier | Alain Serpaggi | 310 | 8th | 5th 1977 | S +2.0 | 8 | | Renault Alpine A442 Renault 2.0L Turbo V6 | Renault Sport | Patrick Depailler | 289 | DNF | DNF 1978 | S +2.0 | 10 | | Mirage M9 Renault 2.0L Turbo V6 | Grand Touring Cars Inc. | Vern Schuppan Sam Posey | 293 | 10th | 5th 1990 | C1 | 6 | G | Porsche 962C Porsche Type-935 3.0L Turbo Flat-6 | Joest Porsche Racing | Henri Pescarolo Jean-Louis Ricci | 328 | 14th | 14th 1993 | GT | 71 | D | Venturi 500LM Renault PRV 3.0 L Turbo V6 | Jacadi Racing | Michel Maisonneuve Christophe Dechavanne | 210 | DNF | DNF 1994 | GT2 | 49 | P | Porsche 911 Carrera RSR Porsche 3.8 L Flat-6 | Larbre Compétition | Jacques Alméras Jean-Marie Alméras | 94 | DNF | DNF 1996 | GT1 | 38 | M | McLaren F1 GTR BMW S70 6.1L V12 | Team Bigazzi SRL | Steve Soper Marc Duez | 318 | 11th | 9th
This image displays a table. Could you provide me with the row number and column number corresponding to this table? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_291
WTQ_203-csv_39.jpg
How many rows and columns does this table contain? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Name | Country | Town | Height metres / ft | Structural type | Held record | Notes Great Pyramid of Giza | Egypt | Giza | 146 / 480 | Mausoleum | 2570 BC–1311 | Due to erosion today it stands at the height of 138.8 metres (455 ft). Lincoln Cathedral | England | Lincoln | 159.7 / 524 | Church | 1311–1549 | Spire collapsed in 1549; today, stands at a height of 83 metres (272 ft). St. Mary's Church | Germany | Stralsund | 151 / 500 | Church | 1549–1647 | Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341 ft). Strasbourg Cathedral | Germany and/or France (today France) | Strasbourg | 142 / 470 | Church | 1647–1874 | St Nikolai | Germany | Hamburg | 147.3 / 483 | Church | 1874–1876 | Due to aerial bombing in World War II the nave was demolished; only the spire remains. Notre-Dame Cathedral | France | Rouen | 151 / 500 | Church | 1876–1880 | Cologne Cathedral | Germany | Cologne | 157.4 / 516 | Church | 1880–1884 | Washington Monument | United States | Washington, D.C. | 169.3 / 555 | Monument | 1884–1889 | Eiffel Tower | France | Paris | 300.6 / 986 | Tower | 1889–1930 | Currently stands at a height of 324 metres (1,063 ft). Chrysler Building | United States | New York City | 319 / 1,046 | Skyscraper | 1930–1931 | Empire State Building | United States | New York City | 448 / 1,472 | Skyscraper | 1931–1967 | Ostankino Tower | Russia | Moscow | 540 / 1,772 | Tower | 1967–1976 | CN Tower | Canada | Toronto | 553 / 1,815 | Tower | 1976–2007 | Burj Khalifa | United Arab Emirates | Dubai | 829.8 / 2,722 | Skyscraper | 2007–present | Topped-out on 17 January 2009
WTQ_for_TSD
Name | Country | Town | Height metres / ft | Structural type | Held record | Notes Great Pyramid of Giza | Egypt | Giza | 146 / 480 | Mausoleum | 2570 BC–1311 | Due to erosion today it stands at the height of 138.8 metres (455 ft). Lincoln Cathedral | England | Lincoln | 159.7 / 524 | Church | 1311–1549 | Spire collapsed in 1549; today, stands at a height of 83 metres (272 ft). St. Mary's Church | Germany | Stralsund | 151 / 500 | Church | 1549–1647 | Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341 ft). Strasbourg Cathedral | Germany and/or France (today France) | Strasbourg | 142 / 470 | Church | 1647–1874 | St Nikolai | Germany | Hamburg | 147.3 / 483 | Church | 1874–1876 | Due to aerial bombing in World War II the nave was demolished; only the spire remains. Notre-Dame Cathedral | France | Rouen | 151 / 500 | Church | 1876–1880 | Cologne Cathedral | Germany | Cologne | 157.4 / 516 | Church | 1880–1884 | Washington Monument | United States | Washington, D.C. | 169.3 / 555 | Monument | 1884–1889 | Eiffel Tower | France | Paris | 300.6 / 986 | Tower | 1889–1930 | Currently stands at a height of 324 metres (1,063 ft). Chrysler Building | United States | New York City | 319 / 1,046 | Skyscraper | 1930–1931 | Empire State Building | United States | New York City | 448 / 1,472 | Skyscraper | 1931–1967 | Ostankino Tower | Russia | Moscow | 540 / 1,772 | Tower | 1967–1976 | CN Tower | Canada | Toronto | 553 / 1,815 | Tower | 1976–2007 | Burj Khalifa | United Arab Emirates | Dubai | 829.8 / 2,722 | Skyscraper | 2007–present | Topped-out on 17 January 2009
How many rows and columns does this table contain? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.
TSD_test_item_292
WTQ_202-csv_48.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}. <TAB> Rank | Airport | Passengers handled | Change 2011/12 1 | London Heathrow | 828,531 | 0% 2 | London Gatwick | 607,417 | 7% 3 | London Stansted | 331,607 | 3% 4 | London Luton | 276,488 | 0% 5 | Belfast International | 266,987 | 8% 6 | Bristol | 239,666 | 8% 7 | Birmingham | 208,123 | 2% 8 | Southampton | 173,576 | 24% 9 | London City | 158,239 | 6% 10 | Belfast City | 100,003 | 4%
WTQ_for_TSD
Rank | Airport | Passengers handled | Change 2011/12 1 | London Heathrow | 828,531 | 0% 2 | London Gatwick | 607,417 | 7% 3 | London Stansted | 331,607 | 3% 4 | London Luton | 276,488 | 0% 5 | Belfast International | 266,987 | 8% 6 | Bristol | 239,666 | 8% 7 | Birmingham | 208,123 | 2% 8 | Southampton | 173,576 | 24% 9 | London City | 158,239 | 6% 10 | Belfast City | 100,003 | 4%
This is a table picture. Can you figure out the row and column numbers for this particular table? Your final answer should be in the JSON structure, formatted as {"row_number": "m", "column_number": "n"}.
TSD_test_item_293
WTQ_203-csv_243.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}. <TAB> Name | Nationality | From | To | Honours | Comments Henrik Jensen | Denmark | 1 July 2012 | Present | | John 'Tune' Kristiansen | Denmark | 18 June 2012 | 23 June 2012 | | Caretaker for one league match Peer F. Hansen | Denmark | 1 January 2012 | 18 June 2012 | won promotion to the third tier | John 'Tune' Kristiansen | Denmark | 27 July 2010 | 30 December 2011 | won promotion to the fourth tier | Originally had contract until summer 2012 René Heitmann | Denmark | 17 July 2010 | 27 July 2010 | | Never coached the team in a match Christian Andersen | Denmark | 11 July 2009 | 19 June 2010 | Team was relegated to third tier | Club went bankrupt after the season Anders Theil | Denmark | 7 November 2005 | 7 July 2009 | | Originally had contract until summer 2011 Ebbe Skovdahl | Denmark | 11 October 2003 | 6 November 2005 | Team was relegated to second tier | Originally had contract until summer 2007 Ole Mørk | Denmark | 15 October 2001 | 10 October 2003 | Won promotion to first tier | Originally had contract until end of 2004 Johnny Petersen | Denmark | 5 May 1998 | 14 October 2001 | | Originally had contract until end of 2001 John 'Tune' Kristiansen | Denmark | 1996 | 4 May 1998 | Won promotion to second tier |
WTQ_for_TSD
Name | Nationality | From | To | Honours | Comments Henrik Jensen | Denmark | 1 July 2012 | Present | | John 'Tune' Kristiansen | Denmark | 18 June 2012 | 23 June 2012 | | Caretaker for one league match Peer F. Hansen | Denmark | 1 January 2012 | 18 June 2012 | won promotion to the third tier | John 'Tune' Kristiansen | Denmark | 27 July 2010 | 30 December 2011 | won promotion to the fourth tier | Originally had contract until summer 2012 René Heitmann | Denmark | 17 July 2010 | 27 July 2010 | | Never coached the team in a match Christian Andersen | Denmark | 11 July 2009 | 19 June 2010 | Team was relegated to third tier | Club went bankrupt after the season Anders Theil | Denmark | 7 November 2005 | 7 July 2009 | | Originally had contract until summer 2011 Ebbe Skovdahl | Denmark | 11 October 2003 | 6 November 2005 | Team was relegated to second tier | Originally had contract until summer 2007 Ole Mørk | Denmark | 15 October 2001 | 10 October 2003 | Won promotion to first tier | Originally had contract until end of 2004 Johnny Petersen | Denmark | 5 May 1998 | 14 October 2001 | | Originally had contract until end of 2001 John 'Tune' Kristiansen | Denmark | 1996 | 4 May 1998 | Won promotion to second tier |
For the table shown in this image, can you tell me the row and column numbers of this table? Provide the final answer in the JSON structure, using the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_294
WTQ_204-csv_254.jpg
For the shown table, how many rows and columns are there? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}. <TAB> Match | Date | Venue | Opponents | Score GL-A-1 | 2006.. | [[]] | [[]] | - GL-A-2 | 2006.. | [[]] | [[]] | - GL-A-3 | 2006.. | [[]] | [[]] | - GL-A-4 | 2006.. | [[]] | [[]] | - GL-A-5 | 2006.. | [[]] | [[]] | - GL-A-6 | 2006.. | [[]] | [[]] | - Quarterfinals-1 | 2006.. | [[]] | [[]] | - Quarterfinals-2 | 2006.. | [[]] | [[]] | - Semifinals-1 | 2006.. | [[]] | [[]] | - Semifinals-2 | 2006.. | [[]] | [[]] | -
WTQ_for_TSD
Match | Date | Venue | Opponents | Score GL-A-1 | 2006.. | [[]] | [[]] | - GL-A-2 | 2006.. | [[]] | [[]] | - GL-A-3 | 2006.. | [[]] | [[]] | - GL-A-4 | 2006.. | [[]] | [[]] | - GL-A-5 | 2006.. | [[]] | [[]] | - GL-A-6 | 2006.. | [[]] | [[]] | - Quarterfinals-1 | 2006.. | [[]] | [[]] | - Quarterfinals-2 | 2006.. | [[]] | [[]] | - Semifinals-1 | 2006.. | [[]] | [[]] | - Semifinals-2 | 2006.. | [[]] | [[]] | -
For the shown table, how many rows and columns are there? Present the final answer in a JSON format {"row_number": "m", "column_number": "n"} such as {"row_number": "2", "column_number": "3"}.
TSD_test_item_295
WTQ_203-csv_63.jpg
How many rows and columns does this table contain? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result. <TAB> Year | Award | Nominated work | Category | Result 2007 | Cosmopolitan Ultimate Woman of the Year | Leona Lewis | Newcomer of the Year | Won 2007 | The Record of the Year | \Bleeding Love\"" | The Record of the Year | Won 2008 | Capital Awards | Leona Lewis | Favourite UK Female Artist | Won 2008 | Britain's Best | Leona Lewis | Music Award | Won 2008 | NewNowNext Awards | Leona Lewis | The Kylie Award: Next International Crossover | Won 2008 | Glamour Woman Of The Year Awards | Leona Lewis | UK Solo Artist | Won 2008 | Nickelodeon UK Kids Choice Awards | \Bleeding Love\"" | Favourite Song | Won 2008 | UK Music Video Awards | \Bleeding Love\"" | People's Choice Award | Won 2008 | Bambi Award | Leona Lewis | Shooting Star | Won 2008 | New Music Weekly Awards | Leona Lewis | Top 40 New Artist of the Year | Won 2008 | Billboard 2008 Year End Award | Leona Lewis | Best New Artist | Won 2008 | Vh1 Video of the Year | \Bleeding Love\"" | Best Video | Won 2008 | NME Best Album | \Spirit\"" | Best Album | Nominated 2008 | PETA | Leona Lewis | Person Of The Year | Won 2009 | NAACP Image Awards | Leona Lewis | Outstanding New Artist | Nominated 2009 | Swiss Music Awards | Leona Lewis | Best International Newcomer | Won 2009 | Japan Gold Disc Awards | Leona Lewis | New Artist Of The Year | Won 2009 | HITO Pop Music Awards | \Bleeding Love\"" | Best Western Song | Won 2009 | PETA - Sexiest Vegetarian Alive Awards | Leona Lewis | Sexiest Vegetarian Celebrity 2009 | Won 2009 | APRA Awards | \Bleeding Love\"" | Most Played Foreign Work | Won 2009 | BEFFTA Awards | Leona Lewis | Best Female Act | Won 2009 | Cosmopolitan Awards | Leona Lewis | Ultimate Music Star | Won
WTQ_for_TSD
Year | Award | Nominated work | Category | Result 2007 | Cosmopolitan Ultimate Woman of the Year | Leona Lewis | Newcomer of the Year | Won 2007 | The Record of the Year | \Bleeding Love\"" | The Record of the Year | Won 2008 | Capital Awards | Leona Lewis | Favourite UK Female Artist | Won 2008 | Britain's Best | Leona Lewis | Music Award | Won 2008 | NewNowNext Awards | Leona Lewis | The Kylie Award: Next International Crossover | Won 2008 | Glamour Woman Of The Year Awards | Leona Lewis | UK Solo Artist | Won 2008 | Nickelodeon UK Kids Choice Awards | \Bleeding Love\"" | Favourite Song | Won 2008 | UK Music Video Awards | \Bleeding Love\"" | People's Choice Award | Won 2008 | Bambi Award | Leona Lewis | Shooting Star | Won 2008 | New Music Weekly Awards | Leona Lewis | Top 40 New Artist of the Year | Won 2008 | Billboard 2008 Year End Award | Leona Lewis | Best New Artist | Won 2008 | Vh1 Video of the Year | \Bleeding Love\"" | Best Video | Won 2008 | NME Best Album | \Spirit\"" | Best Album | Nominated 2008 | PETA | Leona Lewis | Person Of The Year | Won 2009 | NAACP Image Awards | Leona Lewis | Outstanding New Artist | Nominated 2009 | Swiss Music Awards | Leona Lewis | Best International Newcomer | Won 2009 | Japan Gold Disc Awards | Leona Lewis | New Artist Of The Year | Won 2009 | HITO Pop Music Awards | \Bleeding Love\"" | Best Western Song | Won 2009 | PETA - Sexiest Vegetarian Alive Awards | Leona Lewis | Sexiest Vegetarian Celebrity 2009 | Won 2009 | APRA Awards | \Bleeding Love\"" | Most Played Foreign Work | Won 2009 | BEFFTA Awards | Leona Lewis | Best Female Act | Won 2009 | Cosmopolitan Awards | Leona Lewis | Ultimate Music Star | Won
How many rows and columns does this table contain? The JSON format {"row_number": "m", "column_number": "n"} should be utilized to display the ultimate result.
TSD_test_item_296
WTQ_203-csv_666.jpg
Tell me how many rows and columns exist in the given table. Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"} <TAB> Naturalisations by origin | 2000 | 2005 | 2009 | % Total 2009 Africa | 84 182 | 98 453 | 85 144 | 62.7 Maghreb | 68 185 | 75 224 | 56 024 | 41.2 Sub-Saharan Africa | 10 622 | 15 624 | 22 214 | 16.4 Other Africa | 5 375 | 7 605 | 6 906 | 5.1 Asia | 27 941 | 26 286 | 19 494 | 14.4 South-East Asia | 7 265 | 4 069 | 2 475 | 1.8 East Asia | 1 139 | 1 280 | 1 622 | 1.2 South Asia | 4 246 | 4 436 | 3 660 | 2.7 Other Asia | 15 291 | 16 501 | 11 737 | 8.6 Europe (not including CIS ) | 22 085 | 18 072 | 14 753 | 10.9 CIS | 1 181 | 2 108 | 4 704 | 3.5 CIS (Europe) | 1 000 | 1 535 | 4 454 | 3.3 CIS (Asia) | 181 | 573 | 250 | 0.2 America | 5 668 | 6 352 | 6 677 | 4.9 North America | 1 048 | 854 | 747 | 0.5 South and Central America | 4 620 | 5 498 | 5 930 | 4.4 Oceania | 87 | 127 | 108 | 0.1 Others | 8 882 | 3 245 | 4 962 | 3.7 Total | 150 026 | 154 643 | 135 842 | 100
WTQ_for_TSD
Naturalisations by origin | 2000 | 2005 | 2009 | % Total 2009 Africa | 84 182 | 98 453 | 85 144 | 62.7 Maghreb | 68 185 | 75 224 | 56 024 | 41.2 Sub-Saharan Africa | 10 622 | 15 624 | 22 214 | 16.4 Other Africa | 5 375 | 7 605 | 6 906 | 5.1 Asia | 27 941 | 26 286 | 19 494 | 14.4 South-East Asia | 7 265 | 4 069 | 2 475 | 1.8 East Asia | 1 139 | 1 280 | 1 622 | 1.2 South Asia | 4 246 | 4 436 | 3 660 | 2.7 Other Asia | 15 291 | 16 501 | 11 737 | 8.6 Europe (not including CIS ) | 22 085 | 18 072 | 14 753 | 10.9 CIS | 1 181 | 2 108 | 4 704 | 3.5 CIS (Europe) | 1 000 | 1 535 | 4 454 | 3.3 CIS (Asia) | 181 | 573 | 250 | 0.2 America | 5 668 | 6 352 | 6 677 | 4.9 North America | 1 048 | 854 | 747 | 0.5 South and Central America | 4 620 | 5 498 | 5 930 | 4.4 Oceania | 87 | 127 | 108 | 0.1 Others | 8 882 | 3 245 | 4 962 | 3.7 Total | 150 026 | 154 643 | 135 842 | 100
Tell me how many rows and columns exist in the given table. Output the final answer in the JSON format {"row_number": "m", "column_number": "n"}. For instance, if the table has 5 rows and 4 columns, the answer would be {"row_number": "5", "column_number": "4"}
TSD_test_item_297
WTQ_203-csv_708.jpg
For the table shown in this image, can you tell me the row and column numbers of this table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}. <TAB> Date | Opponent# | Rank# | Site | TV | Result | Attendance September 12 | #7 Nebraska* | | Kinnick Stadium • Iowa City, IA | | W 10-7 | 60,160 September 19 | at Iowa State* | | Cyclone Stadium • Ames, IA (Cy-Hawk Trophy) | | L 12-23 | 53,922 September 26 | #6 UCLA* | | Kinnick Stadium • Iowa City, IA | | W 20-7 | 60,004 October 3 | at Northwestern | #18 | Dyche Stadium • Evanston, IL | | W 64-0 | 30,113 October 10 | Indiana | #15 | Kinnick Stadium • Iowa City, IA | | W 42-28 | 60,000 October 17 | at #5 Michigan | #12 | Michigan Stadium • Ann Arbor, MI | | W 9-7 | 105,915 October 24 | Minnesota | #6 | Kinnick Stadium • Iowa City, IA (Floyd of Rosedale) | ABC | L 10-12 | 60,000 October 31 | at Illinois | #16 | Memorial Stadium • Champaign, IL | | L 7-24 | 66,877 November 7 | Purdue | | Kinnick Stadium • Iowa City, IA | | W 33-7 | 60,114 November 14 | at Wisconsin | | Camp Randall Stadium • Madison, WI | ABC | W 17-7 | 78,731 November 21 | Michigan State | #19 | Kinnick Stadium • Iowa City, IA | | W 36-7 | 60,103 January 1 | vs. #12 Washington* | #13 | Rose Bowl • Pasadena, CA (Rose Bowl) | NBC | L 0-28 | 105,611
WTQ_for_TSD
Date | Opponent# | Rank# | Site | TV | Result | Attendance September 12 | #7 Nebraska* | | Kinnick Stadium • Iowa City, IA | | W 10-7 | 60,160 September 19 | at Iowa State* | | Cyclone Stadium • Ames, IA (Cy-Hawk Trophy) | | L 12-23 | 53,922 September 26 | #6 UCLA* | | Kinnick Stadium • Iowa City, IA | | W 20-7 | 60,004 October 3 | at Northwestern | #18 | Dyche Stadium • Evanston, IL | | W 64-0 | 30,113 October 10 | Indiana | #15 | Kinnick Stadium • Iowa City, IA | | W 42-28 | 60,000 October 17 | at #5 Michigan | #12 | Michigan Stadium • Ann Arbor, MI | | W 9-7 | 105,915 October 24 | Minnesota | #6 | Kinnick Stadium • Iowa City, IA (Floyd of Rosedale) | ABC | L 10-12 | 60,000 October 31 | at Illinois | #16 | Memorial Stadium • Champaign, IL | | L 7-24 | 66,877 November 7 | Purdue | | Kinnick Stadium • Iowa City, IA | | W 33-7 | 60,114 November 14 | at Wisconsin | | Camp Randall Stadium • Madison, WI | ABC | W 17-7 | 78,731 November 21 | Michigan State | #19 | Kinnick Stadium • Iowa City, IA | | W 36-7 | 60,103 January 1 | vs. #12 Washington* | #13 | Rose Bowl • Pasadena, CA (Rose Bowl) | NBC | L 0-28 | 105,611
For the table shown in this image, can you tell me the row and column numbers of this table? Output the final answer as JSON in the format {"row_number": "m", "column_number": "n"}.
TSD_test_item_298
WTQ_204-csv_272.jpg
Regarding the table displayed, can you identify how many rows and columns it has? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}. <TAB> Date | Competition | Location | Country | Event | Placing | Rider | Nationality 31 October 2008 | 2008–09 World Cup | Manchester | United Kingdom | Sprint | 1 | Victoria Pendleton | GBR 31 October 2008 | 2008–09 World Cup | Manchester | United Kingdom | Keirin | 2 | Jason Kenny | GBR 1 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Sprint | 1 | Jason Kenny | GBR 1 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | 500 m time trial | 1 | Victoria Pendleton | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Team sprint | 1 | Ross Edgar | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Team sprint | 1 | Jason Kenny | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Team sprint | 1 | Jamie Staff | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Keirin | 1 | Victoria Pendleton | GBR 2 November 2008 | 5th International Keirin Event | Manchester | United Kingdom | International keirin | 2 | Ross Edgar | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Team sprint | 1 | Chris Hoy | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Team sprint | 1 | Jason Kenny | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Team sprint | 1 | Jamie Staff | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Sprint | 1 | Victoria Pendleton | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | Keirin | 1 | Chris Hoy | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | Sprint | 1 | Victoria Pendleton | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | Sprint | 1 | Chris Hoy | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | 500 m time trial | 2 | Victoria Pendleton | GBR 1 November 2009 | 2009–10 World Cup | Manchester | United Kingdom | Team sprint | 1 | Ross Edgar | GBR 1 November 2009 | 2009–10 World Cup | Manchester | United Kingdom | Team sprint | 1 | Chris Hoy | GBR 1 November 2009 | 2009–10 World Cup | Manchester | United Kingdom | Team sprint | 1 | Jamie Staff | GBR
WTQ_for_TSD
Date | Competition | Location | Country | Event | Placing | Rider | Nationality 31 October 2008 | 2008–09 World Cup | Manchester | United Kingdom | Sprint | 1 | Victoria Pendleton | GBR 31 October 2008 | 2008–09 World Cup | Manchester | United Kingdom | Keirin | 2 | Jason Kenny | GBR 1 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Sprint | 1 | Jason Kenny | GBR 1 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | 500 m time trial | 1 | Victoria Pendleton | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Team sprint | 1 | Ross Edgar | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Team sprint | 1 | Jason Kenny | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Team sprint | 1 | Jamie Staff | GBR 2 November 2008 | 2008–09 World Cup | Manchester | United Kingdom | Keirin | 1 | Victoria Pendleton | GBR 2 November 2008 | 5th International Keirin Event | Manchester | United Kingdom | International keirin | 2 | Ross Edgar | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Team sprint | 1 | Chris Hoy | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Team sprint | 1 | Jason Kenny | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Team sprint | 1 | Jamie Staff | GBR 13 February 2009 | 2008–09 World Cup | Copenhagen | Denmark | Sprint | 1 | Victoria Pendleton | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | Keirin | 1 | Chris Hoy | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | Sprint | 1 | Victoria Pendleton | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | Sprint | 1 | Chris Hoy | GBR 30 October 2009 | 2009–10 World Cup | Manchester | United Kingdom | 500 m time trial | 2 | Victoria Pendleton | GBR 1 November 2009 | 2009–10 World Cup | Manchester | United Kingdom | Team sprint | 1 | Ross Edgar | GBR 1 November 2009 | 2009–10 World Cup | Manchester | United Kingdom | Team sprint | 1 | Chris Hoy | GBR 1 November 2009 | 2009–10 World Cup | Manchester | United Kingdom | Team sprint | 1 | Jamie Staff | GBR
Regarding the table displayed, can you identify how many rows and columns it has? Return the result as JSON in the format {"row_number": "m", "column_number": "n"}, e.g., {"row_number": "12", "column_number": "7"}.
TSD_test_item_299
WTQ_204-csv_505.jpg
This is a table picture. Can you figure out the row and column numbers for this particular table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}. <TAB> Rank | Player | County | Tally | Total | Opposition 1 | Francis Forde | Galway | 2–8 | 14 | Roscommon 2 | Niall English | Carlow | 1–9 | 12 | Westmeath 3 | Kevin Broderick | Galway | 3–1 | 10 | New York 3 | Gary Kirby | Limerick | 1–7 | 10 | Tipperary 3 | Gary Kirby | Limerick | 0–10 | 10 | Tipperary 6 | Seán McLoughlin | Westmeath | 1–6 | 9 | Carlow 6 | David Martin | Meath | 1–6 | 9 | Offaly 6 | Gary Kirby | Limerick | 0–9 | 9 | Antrim 9 | John Byrne | Carlow | 2–2 | 8 | Westmeath 9 | John Troy | Offaly | 2–2 | 8 | Laois 9 | John Leahy | Tipperary | 2–2 | 8 | Kerry 9 | Tom Dempsey | Wexford | 1–5 | 8 | Offaly 9 | Paul Flynn | Waterford | 1–5 | 8 | Tipperary 9 | Francis Forde | Galway | 1–5 | 8 | New York
WTQ_for_TSD
Rank | Player | County | Tally | Total | Opposition 1 | Francis Forde | Galway | 2–8 | 14 | Roscommon 2 | Niall English | Carlow | 1–9 | 12 | Westmeath 3 | Kevin Broderick | Galway | 3–1 | 10 | New York 3 | Gary Kirby | Limerick | 1–7 | 10 | Tipperary 3 | Gary Kirby | Limerick | 0–10 | 10 | Tipperary 6 | Seán McLoughlin | Westmeath | 1–6 | 9 | Carlow 6 | David Martin | Meath | 1–6 | 9 | Offaly 6 | Gary Kirby | Limerick | 0–9 | 9 | Antrim 9 | John Byrne | Carlow | 2–2 | 8 | Westmeath 9 | John Troy | Offaly | 2–2 | 8 | Laois 9 | John Leahy | Tipperary | 2–2 | 8 | Kerry 9 | Tom Dempsey | Wexford | 1–5 | 8 | Offaly 9 | Paul Flynn | Waterford | 1–5 | 8 | Tipperary 9 | Francis Forde | Galway | 1–5 | 8 | New York
This is a table picture. Can you figure out the row and column numbers for this particular table? Show your final answer in the JSON format {"row_number": "m", "column_number": "n"}.