Dataset Card for "quarel"

Dataset Summary

QuaRel is a crowdsourced dataset of 2771 multiple-choice story questions, including their logical forms.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 0.63 MB
• Size of the generated dataset: 1.53 MB
• Total amount of disk used: 2.17 MB

An example of 'train' looks as follows.

{
    "answer_index": 0,
    "id": "QuaRel_V1_B5_1403",
    "logical_form_pretty": "qrel(time, lower, world1) -> qrel(distance, higher, world2) ; qrel(distance, higher, world1)",
    "logical_forms": ["(infer (time lower world1) (distance higher world2) (distance higher world1))", "(infer (time lower world2) (distance higher world1) (distance higher world2))"],
    "question": "John and Rita are going for a run.  Rita gets tired and takes a break on the park bench.  After twenty minutes in the park, who has run farther? (A) John (B) Rita",
    "world_literals": {
        "world1": ["Rita"],
        "world2": ["John"]
    }
}

Data Fields

The data fields are the same among all splits.

default

• id: a string feature.
• answer_index: a int32 feature.
• logical_forms: a list of string features.
• logical_form_pretty: a string feature.
• world_literals: a dictionary feature containing:
  • world1: a string feature.
  • world2: a string feature.
• question: a string feature.

Data Splits

name	train	validation	test
default	1941	278	552

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@inproceedings{quarel_v1,
    title={QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships},
    author={Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal},
    year={2018},
    journal={arXiv:1805.05377v1}
}

Contributions

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