Task Categories: question-answering
Languages: en
Multilinguality: monolingual
Size Categories: 1M<n<10M
Licenses: unknown
Language Creators: expert-generated
Annotations Creators: no-annotation
Source Datasets: original
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Dataset Card for QaZre

Dataset Summary

A dataset reducing relation extraction to simple reading comprehension questions

Supported Tasks and Leaderboards

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More Information Needed

Dataset Structure

Data Instances


  • Size of downloaded dataset files: 492.15 MB
  • Size of the generated dataset: 1989.22 MB
  • Total amount of disk used: 2481.37 MB

An example of 'validation' looks as follows.

    "answers": [],
    "context": "answer",
    "question": "What is XXX in this question?",
    "relation": "relation_name",
    "subject": "Some entity Here is a bit of context which will explain the question in some way"

Data Fields

The data fields are the same among all splits.


  • relation: a string feature.
  • question: a string feature.
  • subject: a string feature.
  • context: a string feature.
  • answers: a list of string features.

Data Splits

name train validation test
default 8400000 6000 120000

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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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


Citation Information

    title = "Zero-Shot Relation Extraction via Reading Comprehension",
    author = "Levy, Omer  and
      Seo, Minjoon  and
      Choi, Eunsol  and
      Zettlemoyer, Luke",
    booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "",
    doi = "10.18653/v1/K17-1034",
    pages = "333--342",


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

Update on GitHub