
# Dataset Card for "blimp"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:**
- **Repository:** https://github.com/alexwarstadt/blimp
- **Paper:** [BLiMP: The Benchmark of Linguistic Minimal Pairs for English](https://doi.org/10.1162/tacl_a_00321)
- **Paper:** https://arxiv.org/abs/1912.00582
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 29.58 MB
- **Size of the generated dataset:** 11.45 MB
- **Total amount of disk used:** 41.03 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 and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

#### adjunct_island

- **Size of downloaded dataset files:** 0.36 MB
- **Size of the generated dataset:** 0.17 MB
- **Total amount of disk used:** 0.52 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:** 0.44 MB
- **Size of the generated dataset:** 0.14 MB
- **Total amount of disk used:** 0.57 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:** 0.45 MB
- **Size of the generated dataset:** 0.14 MB
- **Total amount of disk used:** 0.59 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:** 0.46 MB
- **Size of the generated dataset:** 0.15 MB
- **Total amount of disk used:** 0.61 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:** 0.43 MB
- **Size of the generated dataset:** 0.13 MB
- **Total amount of disk used:** 0.57 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`: a `string` feature.
- `sentence_bad`: a `string` feature.
- `field`: a `string` feature.
- `linguistics_term`: a `string` feature.
- `UID`: a `string` feature.
- `simple_LM_method`: a `bool` feature.
- `one_prefix_method`: a `bool` feature.
- `two_prefix_method`: a `bool` feature.
- `lexically_identical`: a `bool` feature.
- `pair_id`: a `int32` feature.

#### anaphor_gender_agreement
- `sentence_good`: a `string` feature.
- `sentence_bad`: a `string` feature.
- `field`: a `string` feature.
- `linguistics_term`: a `string` feature.
- `UID`: a `string` feature.
- `simple_LM_method`: a `bool` feature.
- `one_prefix_method`: a `bool` feature.
- `two_prefix_method`: a `bool` feature.
- `lexically_identical`: a `bool` feature.
- `pair_id`: a `int32` feature.

#### anaphor_number_agreement
- `sentence_good`: a `string` feature.
- `sentence_bad`: a `string` feature.
- `field`: a `string` feature.
- `linguistics_term`: a `string` feature.
- `UID`: a `string` feature.
- `simple_LM_method`: a `bool` feature.
- `one_prefix_method`: a `bool` feature.
- `two_prefix_method`: a `bool` feature.
- `lexically_identical`: a `bool` feature.
- `pair_id`: a `int32` feature.

#### animate_subject_passive
- `sentence_good`: a `string` feature.
- `sentence_bad`: a `string` feature.
- `field`: a `string` feature.
- `linguistics_term`: a `string` feature.
- `UID`: a `string` feature.
- `simple_LM_method`: a `bool` feature.
- `one_prefix_method`: a `bool` feature.
- `two_prefix_method`: a `bool` feature.
- `lexically_identical`: a `bool` feature.
- `pair_id`: a `int32` feature.

#### animate_subject_trans
- `sentence_good`: a `string` feature.
- `sentence_bad`: a `string` feature.
- `field`: a `string` feature.
- `linguistics_term`: a `string` feature.
- `UID`: a `string` feature.
- `simple_LM_method`: a `bool` feature.
- `one_prefix_method`: a `bool` feature.
- `two_prefix_method`: a `bool` feature.
- `lexically_identical`: a `bool` feature.
- `pair_id`: a `int32` feature.

### Data Splits

|          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

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

BLiMP is distributed under a [CC-BY](https://creativecommons.org/licenses/by/4.0/) license. Source: https://github.com/alexwarstadt/blimp#license

### Citation Information

```
@article{warstadt2020blimp,
    author = {Warstadt, Alex and Parrish, Alicia and Liu, Haokun and Mohananey, Anhad and Peng, Wei and Wang, Sheng-Fu and Bowman, Samuel R.},
    title = {BLiMP: The Benchmark of Linguistic Minimal Pairs for English},
    journal = {Transactions of the Association for Computational Linguistics},
    volume = {8},
    number = {},
    pages = {377-392},
    year = {2020},
    doi = {10.1162/tacl\_a\_00321},
    URL = {https://doi.org/10.1162/tacl_a_00321},
    eprint = {https://doi.org/10.1162/tacl_a_00321},
    abstract = { We introduce The Benchmark of Linguistic Minimal Pairs (BLiMP),1 a challenge set for evaluating the linguistic knowledge of language models (LMs) on major grammatical phenomena in English. BLiMP consists of 67 individual datasets, each containing 1,000 minimal pairs—that is, pairs of minimally different sentences that contrast in grammatical acceptability and isolate specific phenomenon in syntax, morphology, or semantics. We generate the data according to linguist-crafted grammar templates, and human aggregate agreement with the labels is 96.4\%. We evaluate n-gram, LSTM, and Transformer (GPT-2 and Transformer-XL) LMs by observing whether they assign a higher probability to the acceptable sentence in each minimal pair. We find that state-of-the-art models identify morphological contrasts related to agreement reliably, but they struggle with some subtle semantic and syntactic phenomena, such as negative polarity items and extraction islands. }
}
```

#### Errata 

Some results were misreported in the published TACL version. Please refer to the corrected version on arXiv: https://arxiv.org/abs/1912.00582


### Contributions

Thanks to [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset.
task_categories:text-classification task_ids:acceptability-classification annotations_creators:crowdsourced language_creators:machine-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:en license:cc-by-4.0 arxiv:1912.00582 region:us
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"anaphor_gender_agreement/train-*"}]}, {"config_name": "anaphor_number_agreement", "data_files": [{"split": "train", "path": "anaphor_number_agreement/train-*"}]}, {"config_name": "animate_subject_passive", "data_files": [{"split": "train", "path": "animate_subject_passive/train-*"}]}, {"config_name": "animate_subject_trans", "data_files": [{"split": "train", "path": "animate_subject_trans/train-*"}]}, {"config_name": "causative", "data_files": [{"split": "train", "path": "causative/train-*"}]}, {"config_name": "complex_NP_island", "data_files": [{"split": "train", "path": "complex_NP_island/train-*"}]}, {"config_name": "coordinate_structure_constraint_complex_left_branch", "data_files": [{"split": "train", "path": "coordinate_structure_constraint_complex_left_branch/train-*"}]}, {"config_name": "coordinate_structure_constraint_object_extraction", "data_files": [{"split": "train", "path": "coordinate_structure_constraint_object_extraction/train-*"}]}, {"config_name": "determiner_noun_agreement_1", "data_files": [{"split": "train", "path": "determiner_noun_agreement_1/train-*"}]}, {"config_name": "determiner_noun_agreement_2", "data_files": [{"split": "train", "path": "determiner_noun_agreement_2/train-*"}]}, {"config_name": "determiner_noun_agreement_irregular_1", "data_files": [{"split": "train", "path": "determiner_noun_agreement_irregular_1/train-*"}]}, {"config_name": "determiner_noun_agreement_irregular_2", "data_files": [{"split": "train", "path": "determiner_noun_agreement_irregular_2/train-*"}]}, {"config_name": "determiner_noun_agreement_with_adj_2", "data_files": [{"split": "train", "path": "determiner_noun_agreement_with_adj_2/train-*"}]}, {"config_name": "determiner_noun_agreement_with_adj_irregular_1", "data_files": [{"split": "train", "path": "determiner_noun_agreement_with_adj_irregular_1/train-*"}]}, {"config_name": "determiner_noun_agreement_with_adj_irregular_2", "data_files": [{"split": "train", "path": "determiner_noun_agreement_with_adj_irregular_2/train-*"}]}, {"config_name": "determiner_noun_agreement_with_adjective_1", "data_files": [{"split": "train", "path": "determiner_noun_agreement_with_adjective_1/train-*"}]}, {"config_name": "distractor_agreement_relational_noun", "data_files": [{"split": "train", "path": "distractor_agreement_relational_noun/train-*"}]}, {"config_name": "distractor_agreement_relative_clause", "data_files": [{"split": "train", "path": "distractor_agreement_relative_clause/train-*"}]}, {"config_name": "drop_argument", "data_files": [{"split": "train", "path": "drop_argument/train-*"}]}, {"config_name": "ellipsis_n_bar_1", "data_files": [{"split": "train", "path": "ellipsis_n_bar_1/train-*"}]}, {"config_name": "ellipsis_n_bar_2", "data_files": [{"split": "train", "path": "ellipsis_n_bar_2/train-*"}]}, {"config_name": "existential_there_object_raising", "data_files": [{"split": "train", "path": "existential_there_object_raising/train-*"}]}, {"config_name": "existential_there_quantifiers_1", "data_files": [{"split": "train", "path": "existential_there_quantifiers_1/train-*"}]}, {"config_name": "existential_there_quantifiers_2", "data_files": [{"split": "train", "path": "existential_there_quantifiers_2/train-*"}]}, {"config_name": "existential_there_subject_raising", "data_files": [{"split": "train", "path": "existential_there_subject_raising/train-*"}]}, {"config_name": "expletive_it_object_raising", "data_files": [{"split": "train", "path": "expletive_it_object_raising/train-*"}]}, {"config_name": "inchoative", "data_files": [{"split": "train", "path": "inchoative/train-*"}]}, {"config_name": "intransitive", "data_files": [{"split": "train", "path": "intransitive/train-*"}]}, {"config_name": "irregular_past_participle_adjectives", "data_files": [{"split": "train", "path": "irregular_past_participle_adjectives/train-*"}]}, {"config_name": "irregular_past_participle_verbs", "data_files": [{"split": "train", "path": "irregular_past_participle_verbs/train-*"}]}, {"config_name": "irregular_plural_subject_verb_agreement_1", "data_files": [{"split": "train", "path": "irregular_plural_subject_verb_agreement_1/train-*"}]}, {"config_name": "irregular_plural_subject_verb_agreement_2", "data_files": [{"split": "train", "path": "irregular_plural_subject_verb_agreement_2/train-*"}]}, {"config_name": "left_branch_island_echo_question", "data_files": [{"split": "train", "path": "left_branch_island_echo_question/train-*"}]}, {"config_name": "left_branch_island_simple_question", "data_files": [{"split": "train", "path": "left_branch_island_simple_question/train-*"}]}, {"config_name": "matrix_question_npi_licensor_present", "data_files": [{"split": "train", "path": "matrix_question_npi_licensor_present/train-*"}]}, {"config_name": "npi_present_1", "data_files": [{"split": "train", "path": "npi_present_1/train-*"}]}, {"config_name": "npi_present_2", "data_files": [{"split": "train", "path": "npi_present_2/train-*"}]}, {"config_name": "only_npi_licensor_present", "data_files": [{"split": "train", "path": "only_npi_licensor_present/train-*"}]}, {"config_name": "only_npi_scope", "data_files": [{"split": "train", "path": "only_npi_scope/train-*"}]}, {"config_name": "passive_1", "data_files": [{"split": "train", "path": "passive_1/train-*"}]}, {"config_name": "passive_2", "data_files": [{"split": "train", "path": "passive_2/train-*"}]}, {"config_name": "principle_A_c_command", "data_files": [{"split": "train", "path": "principle_A_c_command/train-*"}]}, {"config_name": "principle_A_case_1", "data_files": [{"split": "train", "path": "principle_A_case_1/train-*"}]}, {"config_name": "principle_A_case_2", "data_files": [{"split": "train", "path": "principle_A_case_2/train-*"}]}, {"config_name": "principle_A_domain_1", "data_files": [{"split": "train", "path": "principle_A_domain_1/train-*"}]}, {"config_name": "principle_A_domain_2", "data_files": [{"split": "train", "path": "principle_A_domain_2/train-*"}]}, {"config_name": "principle_A_domain_3", "data_files": [{"split": "train", "path": "principle_A_domain_3/train-*"}]}, {"config_name": "principle_A_reconstruction", "data_files": [{"split": "train", "path": "principle_A_reconstruction/train-*"}]}, {"config_name": "regular_plural_subject_verb_agreement_1", "data_files": [{"split": "train", "path": "regular_plural_subject_verb_agreement_1/train-*"}]}, {"config_name": "regular_plural_subject_verb_agreement_2", "data_files": [{"split": "train", "path": "regular_plural_subject_verb_agreement_2/train-*"}]}, {"config_name": "sentential_negation_npi_licensor_present", "data_files": [{"split": "train", "path": "sentential_negation_npi_licensor_present/train-*"}]}, {"config_name": "sentential_negation_npi_scope", "data_files": [{"split": "train", "path": "sentential_negation_npi_scope/train-*"}]}, {"config_name": "sentential_subject_island", "data_files": [{"split": "train", "path": "sentential_subject_island/train-*"}]}, {"config_name": "superlative_quantifiers_1", "data_files": [{"split": "train", "path": "superlative_quantifiers_1/train-*"}]}, {"config_name": "superlative_quantifiers_2", "data_files": [{"split": "train", "path": "superlative_quantifiers_2/train-*"}]}, {"config_name": "tough_vs_raising_1", "data_files": [{"split": "train", "path": "tough_vs_raising_1/train-*"}]}, {"config_name": "tough_vs_raising_2", "data_files": [{"split": "train", "path": "tough_vs_raising_2/train-*"}]}, {"config_name": "transitive", "data_files": [{"split": "train", "path": "transitive/train-*"}]}, {"config_name": "wh_island", "data_files": [{"split": "train", "path": "wh_island/train-*"}]}, {"config_name": "wh_questions_object_gap", "data_files": [{"split": "train", "path": "wh_questions_object_gap/train-*"}]}, {"config_name": "wh_questions_subject_gap", "data_files": [{"split": "train", "path": "wh_questions_subject_gap/train-*"}]}, {"config_name": "wh_questions_subject_gap_long_distance", "data_files": [{"split": "train", "path": "wh_questions_subject_gap_long_distance/train-*"}]}, {"config_name": "wh_vs_that_no_gap", "data_files": [{"split": "train", "path": "wh_vs_that_no_gap/train-*"}]}, {"config_name": "wh_vs_that_no_gap_long_distance", "data_files": [{"split": "train", "path": "wh_vs_that_no_gap_long_distance/train-*"}]}, {"config_name": "wh_vs_that_with_gap", "data_files": [{"split": "train", "path": "wh_vs_that_with_gap/train-*"}]}, {"config_name": "wh_vs_that_with_gap_long_distance", "data_files": [{"split": "train", "path": "wh_vs_that_with_gap_long_distance/train-*"}]}]}
TAGS
#task_categories-text-classification #task_ids-acceptability-classification #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-4.0 #arxiv-1912.00582 #region-us 

Dataset Card for "blimp"
========================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splits
* 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
	+ Contributions


Dataset Description
-------------------


* Homepage:
* Repository: URL
* Paper: BLiMP: The Benchmark of Linguistic Minimal Pairs for English
* Paper: URL
* Point of Contact:
* Size of downloaded dataset files: 29.58 MB
* Size of the generated dataset: 11.45 MB
* Total amount of disk used: 41.03 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 and Leaderboards


### Languages


Dataset Structure
-----------------


### Data Instances


#### adjunct\_island


* Size of downloaded dataset files: 0.36 MB
* Size of the generated dataset: 0.17 MB
* Total amount of disk used: 0.52 MB


An example of 'train' looks as follows.


#### anaphor\_gender\_agreement


* Size of downloaded dataset files: 0.44 MB
* Size of the generated dataset: 0.14 MB
* Total amount of disk used: 0.57 MB


An example of 'train' looks as follows.


#### anaphor\_number\_agreement


* Size of downloaded dataset files: 0.45 MB
* Size of the generated dataset: 0.14 MB
* Total amount of disk used: 0.59 MB


An example of 'train' looks as follows.


#### animate\_subject\_passive


* Size of downloaded dataset files: 0.46 MB
* Size of the generated dataset: 0.15 MB
* Total amount of disk used: 0.61 MB


An example of 'train' looks as follows.


#### animate\_subject\_trans


* Size of downloaded dataset files: 0.43 MB
* Size of the generated dataset: 0.13 MB
* Total amount of disk used: 0.57 MB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### adjunct\_island


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature.


#### anaphor\_gender\_agreement


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature.


#### anaphor\_number\_agreement


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature.


#### animate\_subject\_passive


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature.


#### animate\_subject\_trans


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature.


### Data Splits



Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### 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


BLiMP is distributed under a CC-BY license. Source: URL


#### Errata


Some results were misreported in the published TACL version. Please refer to the corrected version on arXiv: URL


### Contributions


Thanks to @lhoestq, @patrickvonplaten, @thomwolf for adding this dataset.



### 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 and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### adjunct\_island


* Size of downloaded dataset files: 0.36 MB
* Size of the generated dataset: 0.17 MB
* Total amount of disk used: 0.52 MB


An example of 'train' looks as follows. #### anaphor\_gender\_agreement


* Size of downloaded dataset files: 0.44 MB
* Size of the generated dataset: 0.14 MB
* Total amount of disk used: 0.57 MB


An example of 'train' looks as follows. #### anaphor\_number\_agreement


* Size of downloaded dataset files: 0.45 MB
* Size of the generated dataset: 0.14 MB
* Total amount of disk used: 0.59 MB


An example of 'train' looks as follows. #### animate\_subject\_passive


* Size of downloaded dataset files: 0.46 MB
* Size of the generated dataset: 0.15 MB
* Total amount of disk used: 0.61 MB


An example of 'train' looks as follows. #### animate\_subject\_trans


* Size of downloaded dataset files: 0.43 MB
* Size of the generated dataset: 0.13 MB
* Total amount of disk used: 0.57 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### adjunct\_island


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### anaphor\_gender\_agreement


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### anaphor\_number\_agreement


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### animate\_subject\_passive


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### animate\_subject\_trans


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### 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


BLiMP is distributed under a CC-BY license. Source: URL #### Errata


Some results were misreported in the published TACL version. Please refer to the corrected version on arXiv: URL ### Contributions


Thanks to @lhoestq, @patrickvonplaten, @thomwolf for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-acceptability-classification #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-cc-by-4.0 #arxiv-1912.00582 #region-us 
 ### 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 and Leaderboards ### Languages


Dataset Structure
----------------- ### Data Instances #### adjunct\_island


* Size of downloaded dataset files: 0.36 MB
* Size of the generated dataset: 0.17 MB
* Total amount of disk used: 0.52 MB


An example of 'train' looks as follows. #### anaphor\_gender\_agreement


* Size of downloaded dataset files: 0.44 MB
* Size of the generated dataset: 0.14 MB
* Total amount of disk used: 0.57 MB


An example of 'train' looks as follows. #### anaphor\_number\_agreement


* Size of downloaded dataset files: 0.45 MB
* Size of the generated dataset: 0.14 MB
* Total amount of disk used: 0.59 MB


An example of 'train' looks as follows. #### animate\_subject\_passive


* Size of downloaded dataset files: 0.46 MB
* Size of the generated dataset: 0.15 MB
* Total amount of disk used: 0.61 MB


An example of 'train' looks as follows. #### animate\_subject\_trans


* Size of downloaded dataset files: 0.43 MB
* Size of the generated dataset: 0.13 MB
* Total amount of disk used: 0.57 MB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### adjunct\_island


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### anaphor\_gender\_agreement


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### anaphor\_number\_agreement


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### animate\_subject\_passive


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. #### animate\_subject\_trans


* 'sentence\_good': a 'string' feature.
* 'sentence\_bad': a 'string' feature.
* 'field': a 'string' feature.
* 'linguistics\_term': a 'string' feature.
* 'UID': a 'string' feature.
* 'simple\_LM\_method': a 'bool' feature.
* 'one\_prefix\_method': a 'bool' feature.
* 'two\_prefix\_method': a 'bool' feature.
* 'lexically\_identical': a 'bool' feature.
* 'pair\_id': a 'int32' feature. ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### 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


BLiMP is distributed under a CC-BY license. Source: URL #### Errata


Some results were misreported in the published TACL version. Please refer to the corrected version on arXiv: URL ### Contributions


Thanks to @lhoestq, @patrickvonplaten, @thomwolf for adding this dataset.