annotations_creators	language_creators	languages	licenses	multilinguality	size_categories	source_datasets	task_categories	task_ids
expert-generated	found	th	cc-by-nc-sa-3.0	monolingual	1K<n<10K	extended|other-thaiqa	question-answering	extractive-qa open-domain-qa

Dataset Card for thaiqa-squad

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • 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

Dataset Description

• Homepage: http://github.com/pythainlp/thaiqa_squad (original thaiqa at https://aiforthai.in.th/)
• Repository: http://github.com/pythainlp/thaiqa_squad
• Paper:
• Leaderboard:
• **Point of Contact:**http://github.com/pythainlp/ (original thaiqa at https://aiforthai.in.th/)

Dataset Summary

thaiqa_squad is an open-domain, extractive question answering dataset (4,000 questions in train and 74 questions in dev) in SQuAD format, originally created by NECTEC from Wikipedia articles and adapted to SQuAD format by PyThaiNLP.

Supported Tasks and Leaderboards

extractive question answering

Languages

Thai

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

	train	valid
# questions	4000	74
# avg words in context	1186.740750	1016.459459
# avg words in question	14.325500	12.743243
# avg words in answer	3.279750	4.608108

Dataset Creation

Curation Rationale

PyThaiNLP created thaiqa_squad as a SQuAD version of thaiqa. thaiqa is part of The 2nd Question answering program from Thai Wikipedia of National Software Contest 2020.

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

Wikipedia authors for contexts and NECTEC for questions and answer annotations

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

NECTEC

Personal and Sensitive Information

All contents are from Wikipedia. No personal and sensitive information is expected to be included.

Considerations for Using the Data

Social Impact of Dataset

• open-domain, extractive question answering in Thai

Discussion of Biases

[More Information Needed]

Other Known Limitations

• The contexts include <doc> tags at start and at the end

Additional Information

Dataset Curators

NECTEC for original thaiqa. SQuAD formattting by PyThaiNLP.

Licensing Information

CC-BY-NC-SA 3.0

Citation Information

[More Information Needed]