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Dataset Card for MKQA: Multilingual Knowledge Questions & Answers
Dataset Summary
MKQA contains 10,000 queries sampled from the Google Natural Questions dataset.
For each query we collect new passage-independent answers. These queries and answers are then human translated into 25 Non-English languages.
Supported Tasks and Leaderboards
question-answering
Languages
Language code | Language name |
---|---|
ar |
Arabic |
da |
Danish |
de |
German |
en |
English |
es |
Spanish |
fi |
Finnish |
fr |
French |
he |
Hebrew |
hu |
Hungarian |
it |
Italian |
ja |
Japanese |
ko |
Korean |
km |
Khmer |
ms |
Malay |
nl |
Dutch |
no |
Norwegian |
pl |
Polish |
pt |
Portuguese |
ru |
Russian |
sv |
Swedish |
th |
Thai |
tr |
Turkish |
vi |
Vietnamese |
zh_cn |
Chinese (Simplified) |
zh_hk |
Chinese (Hong kong) |
zh_tw |
Chinese (Traditional) |
Dataset Structure
Data Instances
An example from the data set looks as follows:
{
'example_id': 563260143484355911,
'queries': {
'en': "who sings i hear you knocking but you can't come in",
'ru': "кто поет i hear you knocking but you can't come in",
'ja': '「 I hear you knocking」は誰が歌っていますか',
'zh_cn': "《i hear you knocking but you can't come in》是谁演唱的",
...
},
'query': "who sings i hear you knocking but you can't come in",
'answers': {'en': [{'type': 'entity',
'entity': 'Q545186',
'text': 'Dave Edmunds',
'aliases': []}],
'ru': [{'type': 'entity',
'entity': 'Q545186',
'text': 'Эдмундс, Дэйв',
'aliases': ['Эдмундс', 'Дэйв Эдмундс', 'Эдмундс Дэйв', 'Dave Edmunds']}],
'ja': [{'type': 'entity',
'entity': 'Q545186',
'text': 'デイヴ・エドモンズ',
'aliases': ['デーブ・エドモンズ', 'デイブ・エドモンズ']}],
'zh_cn': [{'type': 'entity', 'text': '戴维·埃德蒙兹 ', 'entity': 'Q545186'}],
...
},
}
Data Fields
Each example in the dataset contains the unique Natural Questions example_id
, the original English query
, and then queries
and answers
in 26 languages.
Each answer is labelled with an answer type. The breakdown is:
Answer Type | Occurrence |
---|---|
entity |
4221 |
long_answer |
1815 |
unanswerable |
1427 |
date |
1174 |
number |
485 |
number_with_unit |
394 |
short_phrase |
346 |
binary |
138 |
For each language, there can be more than one acceptable textual answer, in order to capture a variety of possible valid answers.
Detailed explanation of fields taken from here
when entity
field is not available it is set to an empty string ''.
when aliases
field is not available it is set to an empty list [].
Data Splits
- Train: 10000
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Google Natural Questions dataset
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[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
Citation Information
@misc{mkqa,
title = {MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering},
author = {Shayne Longpre and Yi Lu and Joachim Daiber},
year = {2020},
URL = {https://arxiv.org/pdf/2007.15207.pdf}
}
Contributions
Thanks to @cceyda for adding this dataset.
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