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Dataset: qasc 🏷
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from datasets import load_dataset dataset = load_dataset("qasc")

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Dataset Card for "qasc"

Table of Contents

Dataset Description

Dataset Summary

QASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice questions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences.

Supported Tasks

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Languages

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Dataset Structure

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

Data Instances

default

  • Size of downloaded dataset files: 1.54 MB
  • Size of the generated dataset: 5.60 MB
  • Total amount of disk used: 7.14 MB

An example of 'validation' looks as follows.

{
    "answerKey": "F",
    "choices": {
        "label": ["A", "B", "C", "D", "E", "F", "G", "H"],
        "text": ["sand", "occurs over a wide range", "forests", "Global warming", "rapid changes occur", "local weather conditions", "measure of motion", "city life"]
    },
    "combinedfact": "Climate is generally described in terms of local weather conditions",
    "fact1": "Climate is generally described in terms of temperature and moisture.",
    "fact2": "Fire behavior is driven by local weather conditions such as winds, temperature and moisture.",
    "formatted_question": "Climate is generally described in terms of what? (A) sand (B) occurs over a wide range (C) forests (D) Global warming (E) rapid changes occur (F) local weather conditions (G) measure of motion (H) city life",
    "id": "3NGI5ARFTT4HNGVWXAMLNBMFA0U1PG",
    "question": "Climate is generally described in terms of what?"
}

Data Fields

The data fields are the same among all splits.

default

  • id: a string feature.
  • question: a string feature.
  • choices: a dictionary feature containing:
    • text: a string feature.
    • label: a string feature.
  • answerKey: a string feature.
  • fact1: a string feature.
  • fact2: a string feature.
  • combinedfact: a string feature.
  • formatted_question: a string feature.

Data Splits Sample Size

name train validation test
default 8134 926 920

Dataset Creation

Curation Rationale

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Source Data

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Annotations

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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

@article{allenai:qasc,
      author    = {Tushar Khot and Peter Clark and Michal Guerquin and Peter Jansen and Ashish Sabharwal},
      title     = {QASC: A Dataset for Question Answering via Sentence Composition},
      journal   = {arXiv:1910.11473v2},
      year      = {2020},
}