README.md

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Dataset Card for "mlqa"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits Sample Size
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://github.com/facebookresearch/MLQA
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 3958.58 MB
• Size of the generated dataset: 867.85 MB
• Total amount of disk used: 4826.43 MB

Dataset Summary

MLQA (MultiLingual Question Answering) is a benchmark dataset for evaluating cross-lingual question answering performance.
MLQA consists of over 5K extractive QA instances (12K in English) in SQuAD format in seven languages - English, Arabic,
German, Spanish, Hindi, Vietnamese and Simplified Chinese. MLQA is highly parallel, with QA instances parallel between
4 different languages on average.

Supported Tasks

More Information Needed

Languages

More Information Needed

Dataset Structure

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

Data Instances

mlqa-translate-test.ar

• Size of downloaded dataset files: 9.61 MB
• Size of the generated dataset: 5.23 MB
• Total amount of disk used: 14.84 MB

An example of 'test' looks as follows.

mlqa-translate-test.de

• Size of downloaded dataset files: 9.61 MB
• Size of the generated dataset: 3.70 MB
• Total amount of disk used: 13.31 MB

An example of 'test' looks as follows.

mlqa-translate-test.es

• Size of downloaded dataset files: 9.61 MB
• Size of the generated dataset: 3.74 MB
• Total amount of disk used: 13.34 MB

An example of 'test' looks as follows.

mlqa-translate-test.hi

• Size of downloaded dataset files: 9.61 MB
• Size of the generated dataset: 4.40 MB
• Total amount of disk used: 14.00 MB

An example of 'test' looks as follows.

mlqa-translate-test.vi

• Size of downloaded dataset files: 9.61 MB
• Size of the generated dataset: 5.72 MB
• Total amount of disk used: 15.33 MB

An example of 'test' looks as follows.

Data Fields

The data fields are the same among all splits.

mlqa-translate-test.ar

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

mlqa-translate-test.de

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

mlqa-translate-test.es

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

mlqa-translate-test.hi

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

mlqa-translate-test.vi

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

Data Splits Sample Size

name	test
mlqa-translate-test.ar	5335
mlqa-translate-test.de	4517
mlqa-translate-test.es	5253
mlqa-translate-test.hi	4918
mlqa-translate-test.vi	5495

Dataset Creation

Curation Rationale

More Information Needed

Source Data

More Information Needed

Annotations

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

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@article{lewis2019mlqa,
  title={MLQA: Evaluating Cross-lingual Extractive Question Answering},
  author={Lewis, Patrick and Oguz, Barlas and Rinott, Ruty and Riedel, Sebastian and Schwenk, Holger},
  journal={arXiv preprint arXiv:1910.07475},
  year={2019}
}

Contributions

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