MultiBLiMP

MultiBLiMP is a massively Multilingual Benchmark for Linguistic Minimal Pairs. The dataset is composed of synthetic pairs generated using Universal Dependencies and UniMorph.

The paper can be found here.

We split the data set by language: each language consists of a single .tsv file. The rows contain many attributes for a particular pair, most important are the sen and wrong_sen fields, which we use for evaluating the language models.

Using MultiBLiMP

To download the final datasets for a given language, you can usethe example code. Make sure to use the ISO 639-3 code, e.g. eng for English (see table below).

from huggingface_hub import hf_hub_download

hf_hub_download(repo_id="jumelet/multiblimp", filename=f"eng/data.tsv", repo_type="dataset", local_dir='hf_cache/')

To run MultiBLiMP on a model, follow the instructions in this repo. Example evaluation code:

python scripts/lm_eval/eval_model.py 
        --model meta-llama/Meta-Llama-3-8B 
        --data_dir hf_cache/eng/ 
        --src_dir multiblimp 
        --results_dir multiblimp_results/ 
        --cache_dir hf_cache

Languages

This table contains the languages covered in MultiBLiMP and the number of items for each language.

ISO Code	Language	n
abk	Abkhazian	40
aqz	Akuntsu	14
sqi	Albanian	243
amh	Amharic	112
grc	Ancient Greek	3695
hbo	Ancient Hebrew	983
apu	Apurinã	28
hye	Armenian	1415
eus	Basque	273
bel	Belarusian	2570
ben	Bengali	21
bho	Bhojpuri	34
bor	Borôro	241
bre	Breton	260
bul	Bulgarian	2458
bua	Buriat	103
cat	Catalan	2284
chu	Church Slavonic	4166
xcl	Classical Armenian	1623
ces	Czech	4256
dan	Danish	50
nld	Dutch	2331
egy	Egyptian (Ancient)	22
eng	English	770
myv	Erzya	464
est	Estonian	2575
fao	Faroese	232
fin	Finnish	2570
fra	French	2548
glg	Galician	753
kat	Georgian	204
deu	German	2298
aln	Gheg Albanian	677
got	Gothic	1579
guj	Gujarati	7
heb	Hebrew	2330
azz	H-P Nahuatl	207
hin	Hindi	1447
hit	Hittite	50
hun	Hungarian	845
isl	Icelandic	2801
gle	Irish	28
ita	Italian	2999
quc	K'iche'	131
xnr	Kangri	86
krl	Karelian	260
kxh	Karo (Ethiopia)	120
kaz	Kazakh	173
kir	Kirghiz	185
koi	Komi-Permyak	43
kpv	Komi-Zyrian	320
lat	Latin	3149
lav	Latvian	3032
lij	Ligurian	254
lit	Lithuanian	1180
olo	Livvi	190
nds	Low German	1774
mkd	Macedonian	39
mar	Marathi	460
frm	Middle French	294
ell	Modern Greek	1096
mdf	Moksha	82
yrl	Nhengatu	720
pcm	Nigerian Pidgin	26
kmr	Northern Kurdish	544
sme	Northern Sami	2536
fro	Old French	1976
orv	Old Russian	4615
ota	Ottoman Turkish	99
fas	Persian	2553
xpg	Phrygian	50
pol	Polish	3272
por	Portuguese	3048
ron	Romanian	2056
rus	Russian	3832
san	Sanskrit	4442
gla	Scottish Gaelic	66
hbs	Serbo-Croatian	3286
sms	Skolt Sami	263
slk	Slovak	4145
slv	Slovenian	4483
spa	Spanish	2541
arb	Standard Arabic	1215
swe	Swedish	201
tam	Tamil	382
ttc	Tektiteko	69
tpn	Tupinambá	9
tur	Turkish	1742
uig	Uighur	758
ukr	Ukrainian	2744
hsb	Upper Sorbian	186
urd	Urdu	550
urb	Urubú-Kaapor	13
uzb	Uzbek	50
vep	Veps	187
wbp	Warlpiri	12
cym	Welsh	1120
hyw	Western Armenian	1153
wol	Wolof	705
sah	Yakut	144
nhi	Tenango Nahuatl	38

Citation Information

@misc{jumelet2025multiblimp10massivelymultilingual,
      title={MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairs}, 
      author={Jaap Jumelet and Leonie Weissweiler and Arianna Bisazza},
      year={2025},
      eprint={2504.02768},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2504.02768}, 
}