Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
acceptability-classification
Languages:
English
Size:
10K - 100K
ArXiv:
License:
File size: 55,569 Bytes
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---
annotations_creators:
- crowdsourced
language_creators:
- machine-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
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task_ids:
- acceptability-classification
paperswithcode_id: blimp
pretty_name: BLiMP
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download_size: 490996
dataset_size: 173259
- config_name: sentential_negation_npi_scope
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
dtype: string
- name: UID
dtype: string
- name: simple_LM_method
dtype: bool
- name: one_prefix_method
dtype: bool
- name: two_prefix_method
dtype: bool
- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 233493
num_examples: 1000
download_size: 614930
dataset_size: 233493
- config_name: sentential_subject_island
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
dtype: string
- name: UID
dtype: string
- name: simple_LM_method
dtype: bool
- name: one_prefix_method
dtype: bool
- name: two_prefix_method
dtype: bool
- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 173827
num_examples: 1000
download_size: 365822
dataset_size: 173827
- config_name: superlative_quantifiers_1
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
dtype: string
- name: UID
dtype: string
- name: simple_LM_method
dtype: bool
- name: one_prefix_method
dtype: bool
- name: two_prefix_method
dtype: bool
- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 160685
num_examples: 1000
download_size: 381189
dataset_size: 160685
- config_name: superlative_quantifiers_2
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
dtype: string
- name: UID
dtype: string
- name: simple_LM_method
dtype: bool
- name: one_prefix_method
dtype: bool
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dtype: bool
- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 160735
num_examples: 1000
download_size: 516120
dataset_size: 160735
- config_name: tough_vs_raising_1
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
dtype: string
- name: UID
dtype: string
- name: simple_LM_method
dtype: bool
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dtype: bool
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dtype: bool
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dtype: bool
- name: pair_id
dtype: int32
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num_examples: 1000
download_size: 343026
dataset_size: 150031
- config_name: tough_vs_raising_2
features:
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dtype: string
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- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 171079
num_examples: 1000
download_size: 364074
dataset_size: 171079
- config_name: transitive
features:
- name: sentence_good
dtype: string
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dtype: string
- name: field
dtype: string
- name: linguistics_term
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- name: pair_id
dtype: int32
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num_examples: 1000
download_size: 460291
dataset_size: 134499
- config_name: wh_island
features:
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- name: pair_id
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dataset_size: 143735
- config_name: wh_questions_object_gap
features:
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dtype: int32
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- config_name: wh_questions_subject_gap
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- name: pair_id
dtype: int32
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- config_name: wh_questions_subject_gap_long_distance
features:
- name: sentence_good
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dataset_size: 269665
- config_name: wh_vs_that_no_gap
features:
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dtype: string
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- name: pair_id
dtype: int32
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- name: train
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num_examples: 1000
download_size: 383262
dataset_size: 190267
- config_name: wh_vs_that_no_gap_long_distance
features:
- name: sentence_good
dtype: string
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dtype: string
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dtype: string
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dtype: string
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dtype: bool
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dtype: bool
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dtype: bool
- name: pair_id
dtype: int32
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- name: train
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num_examples: 1000
download_size: 441429
dataset_size: 248434
- config_name: wh_vs_that_with_gap
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
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dtype: string
- name: simple_LM_method
dtype: bool
- name: one_prefix_method
dtype: bool
- name: two_prefix_method
dtype: bool
- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 174781
num_examples: 1000
download_size: 367776
dataset_size: 174781
- config_name: wh_vs_that_with_gap_long_distance
features:
- name: sentence_good
dtype: string
- name: sentence_bad
dtype: string
- name: field
dtype: string
- name: linguistics_term
dtype: string
- name: UID
dtype: string
- name: simple_LM_method
dtype: bool
- name: one_prefix_method
dtype: bool
- name: two_prefix_method
dtype: bool
- name: lexically_identical
dtype: bool
- name: pair_id
dtype: int32
splits:
- name: train
num_bytes: 232990
num_examples: 1000
download_size: 425985
dataset_size: 232990
configs:
- config_name: adjunct_island
data_files:
- split: train
path: adjunct_island/train-*
- config_name: anaphor_gender_agreement
data_files:
- split: train
path: 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-*
---
# 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)
- **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.
### 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. }
}
```
### Contributions
Thanks to [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset. |