Datasets:
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- ar
- bn
- en
- fi
- id
- ja
- ko
- ru
- sw
- te
- th
license:
- apache-2.0
multilinguality:
- multilingual
size_categories:
- unknown
source_datasets:
- extended|wikipedia
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: tydi-qa
pretty_name: TyDi QA
dataset_info:
- config_name: primary_task
features:
- name: passage_answer_candidates
sequence:
- name: plaintext_start_byte
dtype: int32
- name: plaintext_end_byte
dtype: int32
- name: question_text
dtype: string
- name: document_title
dtype: string
- name: language
dtype: string
- name: annotations
sequence:
- name: passage_answer_candidate_index
dtype: int32
- name: minimal_answers_start_byte
dtype: int32
- name: minimal_answers_end_byte
dtype: int32
- name: yes_no_answer
dtype: string
- name: document_plaintext
dtype: string
- name: document_url
dtype: string
splits:
- name: train
num_bytes: 5550573801
num_examples: 166916
- name: validation
num_bytes: 484380347
num_examples: 18670
download_size: 2912112378
dataset_size: 6034954148
- config_name: secondary_task
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: train
num_bytes: 52948467
num_examples: 49881
- name: validation
num_bytes: 5006433
num_examples: 5077
download_size: 29402238
dataset_size: 57954900
configs:
- config_name: primary_task
data_files:
- split: train
path: primary_task/train-*
- split: validation
path: primary_task/validation-*
- config_name: secondary_task
data_files:
- split: train
path: secondary_task/train-*
- split: validation
path: secondary_task/validation-*
Dataset Card for "tydiqa"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/google-research-datasets/tydiqa
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 3.91 GB
- Size of the generated dataset: 6.10 GB
- Total amount of disk used: 10.00 GB
Dataset Summary
TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs. The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language expresses -- such that we expect models performing well on this set to generalize across a large number of the languages in the world. It contains language phenomena that would not be found in English-only corpora. To provide a realistic information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but don’t know the answer yet, (unlike SQuAD and its descendents) and the data is collected directly in each language without the use of translation (unlike MLQA and XQuAD).
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
primary_task
- Size of downloaded dataset files: 1.95 GB
- Size of the generated dataset: 6.04 GB
- Total amount of disk used: 7.99 GB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"annotations": {
"minimal_answers_end_byte": [-1, -1, -1],
"minimal_answers_start_byte": [-1, -1, -1],
"passage_answer_candidate_index": [-1, -1, -1],
"yes_no_answer": ["NONE", "NONE", "NONE"]
},
"document_plaintext": "\"\\nรองศาสตราจารย์[1] หม่อมราชวงศ์สุขุมพันธุ์ บริพัตร (22 กันยายน 2495 -) ผู้ว่าราชการกรุงเทพมหานครคนที่ 15 อดีตรองหัวหน้าพรรคปร...",
"document_title": "หม่อมราชวงศ์สุขุมพันธุ์ บริพัตร",
"document_url": "\"https://th.wikipedia.org/wiki/%E0%B8%AB%E0%B8%A1%E0%B9%88%E0%B8%AD%E0%B8%A1%E0%B8%A3%E0%B8%B2%E0%B8%8A%E0%B8%A7%E0%B8%87%E0%B8%...",
"language": "thai",
"passage_answer_candidates": "{\"plaintext_end_byte\": [494, 1779, 2931, 3904, 4506, 5588, 6383, 7122, 8224, 9375, 10473, 12563, 15134, 17765, 19863, 21902, 229...",
"question_text": "\"หม่อมราชวงศ์สุขุมพันธุ์ บริพัตร เรียนจบจากที่ไหน ?\"..."
}
secondary_task
- Size of downloaded dataset files: 1.95 GB
- Size of the generated dataset: 58.03 MB
- Total amount of disk used: 2.01 GB
An example of 'validation' looks as follows.
This example was too long and was cropped:
{
"answers": {
"answer_start": [394],
"text": ["بطولتين"]
},
"context": "\"أقيمت البطولة 21 مرة، شارك في النهائيات 78 دولة، وعدد الفرق التي فازت بالبطولة حتى الآن 8 فرق، ويعد المنتخب البرازيلي الأكثر تت...",
"id": "arabic-2387335860751143628-1",
"question": "\"كم عدد مرات فوز الأوروغواي ببطولة كاس العالم لكرو القدم؟\"...",
"title": "قائمة نهائيات كأس العالم"
}
Data Fields
The data fields are the same among all splits.
primary_task
passage_answer_candidates
: a dictionary feature containing:plaintext_start_byte
: aint32
feature.plaintext_end_byte
: aint32
feature.
question_text
: astring
feature.document_title
: astring
feature.language
: astring
feature.annotations
: a dictionary feature containing:passage_answer_candidate_index
: aint32
feature.minimal_answers_start_byte
: aint32
feature.minimal_answers_end_byte
: aint32
feature.yes_no_answer
: astring
feature.
document_plaintext
: astring
feature.document_url
: astring
feature.
secondary_task
id
: astring
feature.title
: astring
feature.context
: astring
feature.question
: astring
feature.answers
: a dictionary feature containing:text
: astring
feature.answer_start
: aint32
feature.
Data Splits
name | train | validation |
---|---|---|
primary_task | 166916 | 18670 |
secondary_task | 49881 | 5077 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
@article{tydiqa,
title = {TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages},
author = {Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}
year = {2020},
journal = {Transactions of the Association for Computational Linguistics}
}
Contributions
Thanks to @thomwolf, @albertvillanova, @lewtun, @patrickvonplaten for adding this dataset.