class_docstr: 处理 **Conll2003** 的数据，处理之后 :class:`~fastNLP.core.DataSet` 中的内容如下：
  
  .. csv-table::
     :header: "raw_words" , "pos", "chunk", "ner", "words", "seq_len"
  
     "[Nadim, Ladki]", "[0, 0]", "[1, 2]", "[1, 2]", "[2, 3]", 2
     "[AL-AIN, United, Arab, ...]", "[1, 2...]", "[3, 4...]", "[3, 4...]", "[4, 5, 6,...]", 6
     "[...]", "[...]", "[...]", "[...]", "[...]", .
  
  其中``words``, ``seq_len`` 是 input; ``pos``, ``chunk``, ``ner``, ``seq_len`` 是 target
  
  :param chunk_encoding_type: ``chunk`` 列使用什么类型的 encoding 方式，支持 ``['bioes', 'bio']`` 两种。
  :param ner_encoding_type: ``ner`` 列使用什么类型的 encoding 方式，支持 ``['bioes', 'bio']`` 两种。
  :param lower: 是否将 ``words`` 小写化后再建立词表，绝大多数情况都不需要设置为 ``True`` 。
  :param num_proc: 处理数据时使用的进程数目。
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code: def __init__(
      self,
      chunk_encoding_type: str = "bioes",
      ner_encoding_type: str = "bioes",
      lower: bool = False,
      num_proc: int = 0,
  ):
      if chunk_encoding_type == "bio":
          self.chunk_convert_tag = iob2
      elif chunk_encoding_type == "bioes":
  
          def func1(tags):
              return iob2bioes(iob2(tags))
  
          # self.chunk_convert_tag = lambda tags: iob2bioes(iob2(tags))
          self.chunk_convert_tag = func1
      else:
          raise ValueError(
              "chunk_encoding_type only supports `bio` and `bioes`."
          )
      if ner_encoding_type == "bio":
          self.ner_convert_tag = iob2
      elif ner_encoding_type == "bioes":
  
          def func2(tags):
              return iob2bioes(iob2(tags))
  
          # self.ner_convert_tag = lambda tags: iob2bioes(iob2(tags))
          self.ner_convert_tag = func2
      else:
          raise ValueError(
              "ner_encoding_type only supports `bio` and `bioes`."
          )
      self.lower = lower
      self.num_proc = num_proc
  
imports: from .pipe import Pipe
  from .utils import _add_chars_field
  from .utils import _indexize, _add_words_field
  from .utils import iob2, iob2bioes
  from fastNLP.io.data_bundle import DataBundle
  from ..loader.conll import Conll2003NERLoader, OntoNotesNERLoader
  from ..loader.conll import PeopleDailyNERLoader, WeiboNERLoader, MsraNERLoader, ConllLoader
  from ...core.vocabulary import Vocabulary
label_desc: Use image node_id 1 to create a new Conll2003Pipe object from inherited base classes: Pipe with example: obj = Conll2003Pipe(chunk_encoding_type, ner_encoding_type, lower, num_proc)