Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
acceptability-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
Dataset Card for "blimp"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/alexwarstadt/blimp/tree/master/
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 28.21 MB
- Size of the generated dataset: 10.92 MB
- Total amount of disk used: 39.13 MB
Dataset Summary
BLiMP is a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each containing 1000 minimal pairs isolating specific contrasts in syntax, morphology, or semantics. The data is automatically generated according to expert-crafted grammars.
Supported Tasks
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
adjunct_island
- Size of downloaded dataset files: 0.34 MB
- Size of the generated dataset: 0.16 MB
- Total amount of disk used: 0.50 MB
An example of 'train' looks as follows.
{
"UID": "tough_vs_raising_1",
"field": "syntax_semantics",
"lexically_identical": false,
"linguistics_term": "control_raising",
"one_prefix_method": false,
"pair_id": 2,
"sentence_bad": "Benjamin's tutor was certain to boast about.",
"sentence_good": "Benjamin's tutor was easy to boast about.",
"simple_LM_method": true,
"two_prefix_method": false
}
anaphor_gender_agreement
- Size of downloaded dataset files: 0.42 MB
- Size of the generated dataset: 0.13 MB
- Total amount of disk used: 0.54 MB
An example of 'train' looks as follows.
{
"UID": "tough_vs_raising_1",
"field": "syntax_semantics",
"lexically_identical": false,
"linguistics_term": "control_raising",
"one_prefix_method": false,
"pair_id": 2,
"sentence_bad": "Benjamin's tutor was certain to boast about.",
"sentence_good": "Benjamin's tutor was easy to boast about.",
"simple_LM_method": true,
"two_prefix_method": false
}
anaphor_number_agreement
- Size of downloaded dataset files: 0.43 MB
- Size of the generated dataset: 0.13 MB
- Total amount of disk used: 0.56 MB
An example of 'train' looks as follows.
{
"UID": "tough_vs_raising_1",
"field": "syntax_semantics",
"lexically_identical": false,
"linguistics_term": "control_raising",
"one_prefix_method": false,
"pair_id": 2,
"sentence_bad": "Benjamin's tutor was certain to boast about.",
"sentence_good": "Benjamin's tutor was easy to boast about.",
"simple_LM_method": true,
"two_prefix_method": false
}
animate_subject_passive
- Size of downloaded dataset files: 0.44 MB
- Size of the generated dataset: 0.14 MB
- Total amount of disk used: 0.58 MB
An example of 'train' looks as follows.
{
"UID": "tough_vs_raising_1",
"field": "syntax_semantics",
"lexically_identical": false,
"linguistics_term": "control_raising",
"one_prefix_method": false,
"pair_id": 2,
"sentence_bad": "Benjamin's tutor was certain to boast about.",
"sentence_good": "Benjamin's tutor was easy to boast about.",
"simple_LM_method": true,
"two_prefix_method": false
}
animate_subject_trans
- Size of downloaded dataset files: 0.41 MB
- Size of the generated dataset: 0.12 MB
- Total amount of disk used: 0.54 MB
An example of 'train' looks as follows.
{
"UID": "tough_vs_raising_1",
"field": "syntax_semantics",
"lexically_identical": false,
"linguistics_term": "control_raising",
"one_prefix_method": false,
"pair_id": 2,
"sentence_bad": "Benjamin's tutor was certain to boast about.",
"sentence_good": "Benjamin's tutor was easy to boast about.",
"simple_LM_method": true,
"two_prefix_method": false
}
Data Fields
The data fields are the same among all splits.
adjunct_island
sentence_good
: astring
feature.sentence_bad
: astring
feature.field
: astring
feature.linguistics_term
: astring
feature.UID
: astring
feature.simple_LM_method
: abool
feature.one_prefix_method
: abool
feature.two_prefix_method
: abool
feature.lexically_identical
: abool
feature.pair_id
: aint32
feature.
anaphor_gender_agreement
sentence_good
: astring
feature.sentence_bad
: astring
feature.field
: astring
feature.linguistics_term
: astring
feature.UID
: astring
feature.simple_LM_method
: abool
feature.one_prefix_method
: abool
feature.two_prefix_method
: abool
feature.lexically_identical
: abool
feature.pair_id
: aint32
feature.
anaphor_number_agreement
sentence_good
: astring
feature.sentence_bad
: astring
feature.field
: astring
feature.linguistics_term
: astring
feature.UID
: astring
feature.simple_LM_method
: abool
feature.one_prefix_method
: abool
feature.two_prefix_method
: abool
feature.lexically_identical
: abool
feature.pair_id
: aint32
feature.
animate_subject_passive
sentence_good
: astring
feature.sentence_bad
: astring
feature.field
: astring
feature.linguistics_term
: astring
feature.UID
: astring
feature.simple_LM_method
: abool
feature.one_prefix_method
: abool
feature.two_prefix_method
: abool
feature.lexically_identical
: abool
feature.pair_id
: aint32
feature.
animate_subject_trans
sentence_good
: astring
feature.sentence_bad
: astring
feature.field
: astring
feature.linguistics_term
: astring
feature.UID
: astring
feature.simple_LM_method
: abool
feature.one_prefix_method
: abool
feature.two_prefix_method
: abool
feature.lexically_identical
: abool
feature.pair_id
: aint32
feature.
Data Splits Sample Size
name | train |
---|---|
adjunct_island | 1000 |
anaphor_gender_agreement | 1000 |
anaphor_number_agreement | 1000 |
animate_subject_passive | 1000 |
animate_subject_trans | 1000 |
Dataset Creation
Curation Rationale
Source Data
Annotations
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@article{warstadt2019blimp,
title={BLiMP: A Benchmark of Linguistic Minimal Pairs for English},
author={Warstadt, Alex and Parrish, Alicia and Liu, Haokun and Mohananey, Anhad and Peng, Wei, and Wang, Sheng-Fu and Bowman, Samuel R},
journal={arXiv preprint arXiv:1912.00582},
year={2019}
}
Contributions
Thanks to @lhoestq, @patrickvonplaten, @thomwolf for adding this dataset.