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---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- other
license:
- unknown
multilinguality:
- monolingual
paperswithcode_id: superglue
pretty_name: SuperGLUE
size_categories:
- 10K<n<100K
source_datasets:
- extended|other
tags:
- superglue
- NLU
- natural language understanding
task_categories:
- text-classification
- token-classification
- question-answering
task_ids:
- natural-language-inference
- word-sense-disambiguation
- coreference-resolution
- extractive-qa
dataset_info:
- config_name: boolq
features:
- name: question
dtype: string
- name: passage
dtype: string
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: 'False'
1: 'True'
splits:
- name: test
num_bytes: 2107997
num_examples: 3245
- name: train
num_bytes: 6179206
num_examples: 9427
- name: validation
num_bytes: 2118505
num_examples: 3270
download_size: 4118001
dataset_size: 10405708
- config_name: cb
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: entailment
1: contradiction
2: neutral
splits:
- name: test
num_bytes: 93660
num_examples: 250
- name: train
num_bytes: 87218
num_examples: 250
- name: validation
num_bytes: 21894
num_examples: 56
download_size: 75482
dataset_size: 202772
- config_name: copa
features:
- name: premise
dtype: string
- name: choice1
dtype: string
- name: choice2
dtype: string
- name: question
dtype: string
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: choice1
1: choice2
splits:
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num_examples: 500
- name: train
num_bytes: 49599
num_examples: 400
- name: validation
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num_examples: 100
download_size: 43986
dataset_size: 122488
- config_name: multirc
features:
- name: paragraph
dtype: string
- name: question
dtype: string
- name: answer
dtype: string
- name: idx
struct:
- name: paragraph
dtype: int32
- name: question
dtype: int32
- name: answer
dtype: int32
- name: label
dtype:
class_label:
names:
0: 'False'
1: 'True'
splits:
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num_examples: 9693
- name: train
num_bytes: 46213579
num_examples: 27243
- name: validation
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num_examples: 4848
download_size: 1116225
dataset_size: 68968948
- config_name: record
features:
- name: passage
dtype: string
- name: query
dtype: string
- name: entities
sequence: string
- name: entity_spans
sequence:
- name: text
dtype: string
- name: start
dtype: int32
- name: end
dtype: int32
- name: answers
sequence: string
- name: idx
struct:
- name: passage
dtype: int32
- name: query
dtype: int32
splits:
- name: test
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num_examples: 10000
- name: train
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num_examples: 100730
- name: validation
num_bytes: 17479084
num_examples: 10000
download_size: 51757880
dataset_size: 213911711
- config_name: rte
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: idx
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- name: label
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class_label:
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0: entailment
1: not_entailment
splits:
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num_examples: 3000
- name: train
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num_examples: 2490
- name: validation
num_bytes: 90899
num_examples: 277
download_size: 750920
dataset_size: 1915443
- config_name: wic
features:
- name: word
dtype: string
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: start1
dtype: int32
- name: start2
dtype: int32
- name: end1
dtype: int32
- name: end2
dtype: int32
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: 'False'
1: 'True'
splits:
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num_examples: 1400
- name: train
num_bytes: 665183
num_examples: 5428
- name: validation
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num_examples: 638
download_size: 396213
dataset_size: 928399
- config_name: wsc
features:
- name: text
dtype: string
- name: span1_index
dtype: int32
- name: span2_index
dtype: int32
- name: span1_text
dtype: string
- name: span2_text
dtype: string
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: 'False'
1: 'True'
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- name: train
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num_examples: 554
- name: validation
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num_examples: 104
download_size: 32751
dataset_size: 143092
- config_name: wsc.fixed
features:
- name: text
dtype: string
- name: span1_index
dtype: int32
- name: span2_index
dtype: int32
- name: span1_text
dtype: string
- name: span2_text
dtype: string
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: 'False'
1: 'True'
splits:
- name: test
num_bytes: 31568
num_examples: 146
- name: train
num_bytes: 89883
num_examples: 554
- name: validation
num_bytes: 21637
num_examples: 104
download_size: 32751
dataset_size: 143088
- config_name: axb
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: idx
dtype: int32
- name: label
dtype:
class_label:
names:
0: entailment
1: not_entailment
splits:
- name: test
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num_examples: 1104
download_size: 33950
dataset_size: 238392
- config_name: axg
features:
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: idx
dtype: int32
- name: label
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class_label:
names:
0: entailment
1: not_entailment
splits:
- name: test
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num_examples: 356
download_size: 10413
dataset_size: 53581
---
# Dataset Card for "super_glue"
## 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:** [https://github.com/google-research-datasets/boolean-questions](https://github.com/google-research-datasets/boolean-questions)
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **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:** 55.66 MB
- **Size of the generated dataset:** 238.01 MB
- **Total amount of disk used:** 293.67 MB
### Dataset Summary
SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after
GLUE with a new set of more difficult language understanding tasks, improved
resources, and a new public leaderboard.
BoolQ (Boolean Questions, Clark et al., 2019a) is a QA task where each example consists of a short
passage and a yes/no question about the passage. The questions are provided anonymously and
unsolicited by users of the Google search engine, and afterwards paired with a paragraph from a
Wikipedia article containing the answer. Following the original work, we evaluate with accuracy.
### 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
#### axb
- **Size of downloaded dataset files:** 0.03 MB
- **Size of the generated dataset:** 0.23 MB
- **Total amount of disk used:** 0.26 MB
An example of 'test' looks as follows.
```
```
#### axg
- **Size of downloaded dataset files:** 0.01 MB
- **Size of the generated dataset:** 0.05 MB
- **Total amount of disk used:** 0.06 MB
An example of 'test' looks as follows.
```
```
#### boolq
- **Size of downloaded dataset files:** 3.93 MB
- **Size of the generated dataset:** 9.92 MB
- **Total amount of disk used:** 13.85 MB
An example of 'train' looks as follows.
```
```
#### cb
- **Size of downloaded dataset files:** 0.07 MB
- **Size of the generated dataset:** 0.19 MB
- **Total amount of disk used:** 0.27 MB
An example of 'train' looks as follows.
```
```
#### copa
- **Size of downloaded dataset files:** 0.04 MB
- **Size of the generated dataset:** 0.12 MB
- **Total amount of disk used:** 0.16 MB
An example of 'train' looks as follows.
```
```
### Data Fields
The data fields are the same among all splits.
#### axb
- `sentence1`: a `string` feature.
- `sentence2`: a `string` feature.
- `idx`: a `int32` feature.
- `label`: a classification label, with possible values including `entailment` (0), `not_entailment` (1).
#### axg
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `idx`: a `int32` feature.
- `label`: a classification label, with possible values including `entailment` (0), `not_entailment` (1).
#### boolq
- `question`: a `string` feature.
- `passage`: a `string` feature.
- `idx`: a `int32` feature.
- `label`: a classification label, with possible values including `False` (0), `True` (1).
#### cb
- `premise`: a `string` feature.
- `hypothesis`: a `string` feature.
- `idx`: a `int32` feature.
- `label`: a classification label, with possible values including `entailment` (0), `contradiction` (1), `neutral` (2).
#### copa
- `premise`: a `string` feature.
- `choice1`: a `string` feature.
- `choice2`: a `string` feature.
- `question`: a `string` feature.
- `idx`: a `int32` feature.
- `label`: a classification label, with possible values including `choice1` (0), `choice2` (1).
### Data Splits
#### axb
| |test|
|---|---:|
|axb|1104|
#### axg
| |test|
|---|---:|
|axg| 356|
#### boolq
| |train|validation|test|
|-----|----:|---------:|---:|
|boolq| 9427| 3270|3245|
#### cb
| |train|validation|test|
|---|----:|---------:|---:|
|cb | 250| 56| 250|
#### copa
| |train|validation|test|
|----|----:|---------:|---:|
|copa| 400| 100| 500|
## 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
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Citation Information
```
@inproceedings{clark2019boolq,
title={BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions},
author={Clark, Christopher and Lee, Kenton and Chang, Ming-Wei, and Kwiatkowski, Tom and Collins, Michael, and Toutanova, Kristina},
booktitle={NAACL},
year={2019}
}
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},
journal={arXiv preprint arXiv:1905.00537},
year={2019}
}
Note that each SuperGLUE dataset has its own citation. Please see the source to
get the correct citation for each contained dataset.
```
### Contributions
Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.