metadata

annotations_creators:
  - expert-generated
language_creators:
  - other
language:
  - en
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - extended|other
task_categories:
  - text-classification
  - token-classification
  - question-answering
task_ids:
  - natural-language-inference
  - word-sense-disambiguation
  - coreference-resolution
  - extractive-qa
pretty_name: SuperGLUE
tags:
  - superglue
  - NLU
  - natural language understanding
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:
      - name: test
        num_bytes: 60303
        num_examples: 500
      - name: train
        num_bytes: 49599
        num_examples: 400
      - name: validation
        num_bytes: 12586
        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:
      - name: test
        num_bytes: 14996451
        num_examples: 9693
      - name: train
        num_bytes: 46213579
        num_examples: 27243
      - name: validation
        num_bytes: 7758918
        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: train
        num_bytes: 179232052
        num_examples: 100730
      - name: validation
        num_bytes: 17479084
        num_examples: 10000
      - name: test
        num_bytes: 17200575
        num_examples: 10000
    download_size: 51757880
    dataset_size: 213911711
  - config_name: rte
    features:
      - name: premise
        dtype: string
      - name: hypothesis
        dtype: string
      - name: idx
        dtype: int32
      - name: label
        dtype:
          class_label:
            names:
              '0': entailment
              '1': not_entailment
    splits:
      - name: test
        num_bytes: 975799
        num_examples: 3000
      - name: train
        num_bytes: 848745
        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:
      - name: test
        num_bytes: 180593
        num_examples: 1400
      - name: train
        num_bytes: 665183
        num_examples: 5428
      - name: validation
        num_bytes: 82623
        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'
    splits:
      - name: test
        num_bytes: 31572
        num_examples: 146
      - name: train
        num_bytes: 89883
        num_examples: 554
      - name: validation
        num_bytes: 21637
        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
        num_bytes: 238392
        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
        dtype:
          class_label:
            names:
              '0': entailment
              '1': not_entailment
    splits:
      - name: test
        num_bytes: 53581
        num_examples: 356
    download_size: 10413
    dataset_size: 53581

Dataset Card for "super_glue"

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://github.com/google-research-datasets/boolean-questions
Repository: More Information Needed
Paper: More Information Needed
Point of Contact: More Information Needed
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

Languages

More Information Needed

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

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

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, @lewtun, @patrickvonplaten for adding this dataset.

Dataset Card for "super_glue"

Table of Contents

Dataset Description

Dataset Summary

Supported Tasks and Leaderboards

Languages

Dataset Structure

Data Instances

axb

axg

boolq

cb

copa

Data Fields

axb

axg

boolq

cb

copa

Data Splits

axb

axg

boolq

cb

copa

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

Citation Information

Contributions