Datasets:
openbookqa

Languages: en

Dataset Card for "openbookqa"

Dataset Summary

OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic (with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In particular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge, and rich text comprehension. OpenBookQA is a new kind of question-answering dataset modeled after open book exams for assessing human understanding of a subject.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

additional

  • Size of downloaded dataset files: 1.38 MB
  • Size of the generated dataset: 1.38 MB
  • Total amount of disk used: 2.75 MB

An example of 'train' looks as follows.


main

  • Size of downloaded dataset files: 1.38 MB
  • Size of the generated dataset: 1.38 MB
  • Total amount of disk used: 2.75 MB

An example of 'validation' looks as follows.


Data Fields

The data fields are the same among all splits.

additional

  • id: a string feature.
  • question_stem: a string feature.
  • choices: a dictionary feature containing:
    • text: a string feature.
    • label: a string feature.
  • answerKey: a string feature.

main

  • id: a string feature.
  • question_stem: a string feature.
  • choices: a dictionary feature containing:
    • text: a string feature.
    • label: a string feature.
  • answerKey: a string feature.

Data Splits

name train validation test
additional 4957 500 500
main 4957 500 500

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

Annotation process

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Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

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Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@inproceedings{OpenBookQA2018,
 title={Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering},
 author={Todor Mihaylov and Peter Clark and Tushar Khot and Ashish Sabharwal},
 booktitle={EMNLP},
 year={2018}
}

Contributions

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

Models trained or fine-tuned on openbookqa