README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
languages:
  ar:
    - ar
  de:
    - de
  el:
    - el
  en:
    - en
  es:
    - es
  hi:
    - hi
  ru:
    - ru
  th:
    - th
  tr:
    - tr
  vi:
    - vi
  zh:
    - zh
licenses:
  - cc-by-sa-4-0
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - extended|squad
  - extended|xquad
task_categories:
  - question-answering
task_ids:
  - extractive-qa
paperswithcode_id: xquad-r

Dataset Card for [Dataset Name]

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• 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: LAReQA
• Repository: XQuAD-R
• Paper: LAReQA: Language-agnostic answer retrieval from a multilingual pool
• Point of Contact: Noah Constant

Dataset Summary

XQuAD-R is a retrieval version of the XQuAD dataset (a cross-lingual extractive QA dataset). Like XQuAD, XQUAD-R is an 11-way parallel dataset, where each question appears in 11 different languages and has 11 parallel correct answers across the languages.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

The dataset can be found with the following languages:

• Arabic: xquad-r/ar.json
• German: xquad-r/de.json
• Greek: xquad-r/el.json
• English: xquad-r/en.json
• Spanish: xquad-r/es.json
• Hindi: xquad-r/hi.json
• Russian: xquad-r/ru.json
• Thai: xquad-r/th.json
• Turkish: xquad-r/tr.json
• Vietnamese: xquad-r/vi.json
• Chinese: xquad-r/zh.json

Dataset Structure

[More Information Needed]

Data Instances

The number of questions and candidate sentences for each language for XQuAD-R is shown in the table below:

	XQuAD-R
	questions	candidates
ar	1190	1222
de	1190	1276
el	1190	1234
en	1190	1180
es	1190	1215
hi	1190	1244
ru	1190	1219
th	1190	852
tr	1190	1167
vi	1190	1209
zh	1190	1196

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

[More Information Needed]

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

[More Information Needed]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

[More Information Needed]

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

[More Information Needed]

Dataset Curators

The dataset was initially created by Uma Roy, Noah Constant, Rami Al-Rfou, Aditya Barua, Aaron Phillips and Yinfei Yang, during work done at Google Research.

Licensing Information

XQuAD-R is distributed under the CC BY-SA 4.0 license.

Citation Information

@article{roy2020lareqa,
  title={LAReQA: Language-agnostic answer retrieval from a multilingual pool},
  author={Roy, Uma and Constant, Noah and Al-Rfou, Rami and Barua, Aditya and Phillips, Aaron and Yang, Yinfei},
  journal={arXiv preprint arXiv:2004.05484},
  year={2020}
}

Contributions

Thanks to @manandey for adding this dataset.