Datasets:
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---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- ar
- da
- de
- en
- es
- fi
- fr
- he
- hu
- it
- ja
- km
- ko
- ms
- nl
- 'no'
- pl
- pt
- ru
- sv
- th
- tr
- vi
- zh
license:
- cc-by-3.0
multilinguality:
- multilingual
- translation
size_categories:
- 10K<n<100K
source_datasets:
- extended|natural_questions
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: mkqa
pretty_name: Multilingual Knowledge Questions and Answers
---
# Dataset Card for MKQA: Multilingual Knowledge Questions & Answers
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- [**Homepage:**](https://github.com/apple/ml-mkqa/)
- [**Paper:**](https://arxiv.org/abs/2007.15207)
### Dataset Summary
MKQA contains 10,000 queries sampled from the [Google Natural Questions dataset](https://github.com/google-research-datasets/natural-questions).
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](https://github.com/apple/ml-mkqa/#dataset)
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](https://github.com/google-research-datasets/natural-questions)
#### 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
[CC BY-SA 3.0](https://github.com/apple/ml-mkqa#license)
### 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](https://github.com/cceyda) for adding this dataset.
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