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Dataset: piaf 🏷
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Table of Contents

Dataset Description

Dataset Summary

Piaf is a reading comprehension dataset. This version, published in February 2020, contains 3835 questions on French Wikipedia.

Supported Tasks

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Dataset Structure

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

Data Instances


  • Size of downloaded dataset files: 1.31 MB
  • Size of the generated dataset: 3.18 MB
  • Total amount of disk used: 4.49 MB

An example of 'train' looks as follows.

    "answers": {
        "answer_start": [0],
        "text": ["Voici"]
    "context": "Voici le contexte du premier paragraphe du deuxième article.",
    "id": "p140295460356960",
    "question": "Suis-je la troisième question ?",
    "title": "Jakob Böhme"

Data Fields

The data fields are the same among all splits.


  • id: a string feature.
  • title: a string feature.
  • context: a string feature.
  • question: a string feature.
  • answers: a dictionary feature containing:
    • text: a string feature.
    • answer_start: a int32 feature.

Data Splits Sample Size

name train
plain_text 3835

Dataset Creation

Curation Rationale

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Source Data

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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

  author    = {Keraron, Rachel  and  Lancrenon, Guillaume  and  Bras, Mathilde  and  Allary, Frédéric  and  Moyse, Gilles  and  Scialom, Thomas  and  Soriano-Morales, Edmundo-Pavel  and  Staiano, Jacopo},
  title     = {Project PIAF: Building a Native French Question-Answering Dataset},
  booktitle      = {Proceedings of The 12th Language Resources and Evaluation Conference},
  month          = {May},
  year           = {2020},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {5483--5492},
  abstract  = {Motivated by the lack of data for non-English languages, in particular for the evaluation of downstream tasks such as Question Answering, we present a participatory effort to collect a native French Question Answering Dataset. Furthermore, we describe and publicly release the annotation tool developed for our collection effort, along with the data obtained and preliminary baselines.},
  url       = {}