
# Dataset Card for JaQuAD

## Table of Contents

- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splitting](#data-splitting)
- [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)
  - [Acknowledgements](#acknowledgements)

## Dataset Description

- **Repository:** https://github.com/SkelterLabsInc/JaQuAD
- **Paper:** [JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehension]()
- **Point of Contact:** [jaquad@skelterlabs.com](jaquad@skelterlabs.com)
- **Size of dataset files:** 24.6 MB
- **Size of the generated dataset:** 48.6 MB
- **Total amount of disk used:** 73.2 MB

### Dataset Summary

Japanese Question Answering Dataset (JaQuAD), released in 2022, is a
human-annotated dataset created for Japanese Machine Reading Comprehension.
JaQuAD is developed to provide a SQuAD-like QA dataset in Japanese.
JaQuAD contains 39,696 question-answer pairs.
Questions and answers are manually curated by human annotators.
Contexts are collected from Japanese Wikipedia articles.
Fine-tuning [BERT-Japanese](https://huggingface.co/cl-tohoku/bert-base-japanese)
on JaQuAD achieves 78.92% for an F1 score and 63.38% for an exact match.

### Supported Tasks

- `extractive-qa`: This dataset is intended to be used for `extractive-qa`.

### Languages

Japanese (`ja`)

## Dataset Structure

### Data Instances

- **Size of dataset files:** 24.6 MB
- **Size of the generated dataset:** 48.6 MB
- **Total amount of disk used:** 73.2 MB

An example of 'validation':
```python
{
    "id": "de-001-00-000",
    "title": "イタセンパラ",
    "context": "イタセンパラ(板鮮腹、Acheilognathuslongipinnis)は、コイ科のタナゴ亜科タナゴ属に分類される淡水>魚の一種。\n別名はビワタナゴ(琵琶鱮、琵琶鰱)。",
    "question": "ビワタナゴの正式名称は何?",
    "question_type": "Multiple sentence reasoning",
    "answers": {
        "text": "イタセンパラ",
        "answer_start": 0,
        "answer_type": "Object",
    },
},
```

### Data Fields

- `id`: a `string` feature.
- `title`: a `string` feature.
- `context`: a `string` feature.
- `question`: a `string` feature.
- `question_type`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.
  - `answer_type`: a `string` feature.

### Data Splitting

JaQuAD consists of three sets, `train`, `validation`, and `test`. They were
created from disjoint sets of Wikipedia articles. The `test` set is not publicly
released yet. The following table shows statistics for each set.

Set | Number of Articles | Number of Contexts | Number of Questions
--------------|--------------------|--------------------|--------------------
Train | 691 | 9713 | 31748
Validation | 101 | 1431 | 3939
Test | 109 | 1479 | 4009


## Dataset Creation

### Curation Rationale

The JaQuAD dataset was created by [Skelter Labs](https://skelterlabs.com/) to
provide a SQuAD-like QA dataset in Japanese. Questions are original and based
on Japanese Wikipedia articles.

### Source Data

The articles used for the contexts are from [Japanese Wikipedia](https://ja.wikipedia.org/).
88.7% of articles are from the curated list of Japanese high-quality Wikipedia
articles, e.g., [featured articles](https://ja.wikipedia.org/wiki/Wikipedia:%E8%89%AF%E8%B3%AA%E3%81%AA%E8%A8%98%E4%BA%8B)
and [good articles](https://ja.wikipedia.org/wiki/Wikipedia:%E7%A7%80%E9%80%B8%E3%81%AA%E8%A8%98%E4%BA%8B).

### Annotations

Wikipedia articles were scrapped and divided into one more multiple paragraphs
as contexts. Annotations (questions and answer spans) are written by fluent
Japanese speakers, including natives and non-natives. Annotators were given a
context and asked to generate non-trivial questions about information in the
context.

### Personal and Sensitive Information

No personal or sensitive information is included in this dataset. Dataset
annotators has been manually verified it.

## Considerations for Using the Data

Users should consider that the articles are sampled from Wikipedia articles but
not representative of all Wikipedia articles.

### Social Impact of Dataset

The social biases of this dataset have not yet been investigated.

### Discussion of Biases

The social biases of this dataset have not yet been investigated. Articles and
questions have been selected for quality and diversity.

### Other Known Limitations

The JaQuAD dataset has limitations as follows:
- Most of them are short answers.
- Assume that a question is answerable using the corresponding context.

This dataset is incomplete yet. If you find any errors in JaQuAD, please contact
us.

## Additional Information

### Dataset Curators

Skelter Labs: [https://skelterlabs.com/](https://skelterlabs.com/)

### Licensing Information

The JaQuAD dataset is licensed under the [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/) license.

### Citation Information

```bibtex
@misc{so2022jaquad,
      title={{JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehension}},
      author={ByungHoon So and Kyuhong Byun and Kyungwon Kang and Seongjin Cho},
      year={2022},
      eprint={2202.01764},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

### Acknowledgements

This work was supported by [TPU Research Cloud (TRC) program](https://sites.research.google/trc/).
For training models, we used cloud TPUs provided by TRC. We also thank
annotators who generated JaQuAD.


task_categories:question-answering task_ids:extractive-qa annotations_creators:crowdsourced language_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:ja license:cc-by-sa-3.0 arxiv:2202.01764 region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced", "found"], "language": ["ja"], "license": ["cc-by-sa-3.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["question-answering"], "task_ids": ["extractive-qa"], "pretty_name": "JaQuAD: Japanese Question Answering Dataset"}
TAGS
#task_categories-question-answering #task_ids-extractive-qa #annotations_creators-crowdsourced #language_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Japanese #license-cc-by-sa-3.0 #arxiv-2202.01764 #region-us 

Dataset Card for JaQuAD
=======================


Table of Contents
-----------------


* Table of Contents
* Dataset Description
	+ Dataset Summary
	+ Supported Tasks
	+ Languages
* Dataset Structure
	+ Data Instances
	+ Data Fields
	+ Data Splitting
* 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
	+ Acknowledgements


Dataset Description
-------------------


* Repository: URL
* Paper: JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehension
* Point of Contact: jaquad@URL
* Size of dataset files: 24.6 MB
* Size of the generated dataset: 48.6 MB
* Total amount of disk used: 73.2 MB


### Dataset Summary


Japanese Question Answering Dataset (JaQuAD), released in 2022, is a
human-annotated dataset created for Japanese Machine Reading Comprehension.
JaQuAD is developed to provide a SQuAD-like QA dataset in Japanese.
JaQuAD contains 39,696 question-answer pairs.
Questions and answers are manually curated by human annotators.
Contexts are collected from Japanese Wikipedia articles.
Fine-tuning BERT-Japanese
on JaQuAD achieves 78.92% for an F1 score and 63.38% for an exact match.


### Supported Tasks


* 'extractive-qa': This dataset is intended to be used for 'extractive-qa'.


### Languages


Japanese ('ja')


Dataset Structure
-----------------


### Data Instances


* Size of dataset files: 24.6 MB
* Size of the generated dataset: 48.6 MB
* Total amount of disk used: 73.2 MB


An example of 'validation':


### Data Fields


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'question\_type': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature.
	+ 'answer\_type': a 'string' feature.


### Data Splitting


JaQuAD consists of three sets, 'train', 'validation', and 'test'. They were
created from disjoint sets of Wikipedia articles. The 'test' set is not publicly
released yet. The following table shows statistics for each set.



Dataset Creation
----------------


### Curation Rationale


The JaQuAD dataset was created by Skelter Labs to
provide a SQuAD-like QA dataset in Japanese. Questions are original and based
on Japanese Wikipedia articles.


### Source Data


The articles used for the contexts are from Japanese Wikipedia.
88.7% of articles are from the curated list of Japanese high-quality Wikipedia
articles, e.g., featured articles
and good articles.


### Annotations


Wikipedia articles were scrapped and divided into one more multiple paragraphs
as contexts. Annotations (questions and answer spans) are written by fluent
Japanese speakers, including natives and non-natives. Annotators were given a
context and asked to generate non-trivial questions about information in the
context.


### Personal and Sensitive Information


No personal or sensitive information is included in this dataset. Dataset
annotators has been manually verified it.


Considerations for Using the Data
---------------------------------


Users should consider that the articles are sampled from Wikipedia articles but
not representative of all Wikipedia articles.


### Social Impact of Dataset


The social biases of this dataset have not yet been investigated.


### Discussion of Biases


The social biases of this dataset have not yet been investigated. Articles and
questions have been selected for quality and diversity.


### Other Known Limitations


The JaQuAD dataset has limitations as follows:


* Most of them are short answers.
* Assume that a question is answerable using the corresponding context.


This dataset is incomplete yet. If you find any errors in JaQuAD, please contact
us.


Additional Information
----------------------


### Dataset Curators


Skelter Labs: URL


### Licensing Information


The JaQuAD dataset is licensed under the CC BY-SA 3.0 license.


### Acknowledgements


This work was supported by TPU Research Cloud (TRC) program.
For training models, we used cloud TPUs provided by TRC. We also thank
annotators who generated JaQuAD.



### Dataset Summary


Japanese Question Answering Dataset (JaQuAD), released in 2022, is a
human-annotated dataset created for Japanese Machine Reading Comprehension.
JaQuAD is developed to provide a SQuAD-like QA dataset in Japanese.
JaQuAD contains 39,696 question-answer pairs.
Questions and answers are manually curated by human annotators.
Contexts are collected from Japanese Wikipedia articles.
Fine-tuning BERT-Japanese
on JaQuAD achieves 78.92% for an F1 score and 63.38% for an exact match. ### Supported Tasks


* 'extractive-qa': This dataset is intended to be used for 'extractive-qa'. ### Languages


Japanese ('ja')


Dataset Structure
----------------- ### Data Instances


* Size of dataset files: 24.6 MB
* Size of the generated dataset: 48.6 MB
* Total amount of disk used: 73.2 MB


An example of 'validation': ### Data Fields


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'question\_type': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature.
	+ 'answer\_type': a 'string' feature. ### Data Splitting


JaQuAD consists of three sets, 'train', 'validation', and 'test'. They were
created from disjoint sets of Wikipedia articles. The 'test' set is not publicly
released yet. The following table shows statistics for each set.



Dataset Creation
---------------- ### Curation Rationale


The JaQuAD dataset was created by Skelter Labs to
provide a SQuAD-like QA dataset in Japanese. Questions are original and based
on Japanese Wikipedia articles. ### Source Data


The articles used for the contexts are from Japanese Wikipedia.
88.7% of articles are from the curated list of Japanese high-quality Wikipedia
articles, e.g., featured articles
and good articles. ### Annotations


Wikipedia articles were scrapped and divided into one more multiple paragraphs
as contexts. Annotations (questions and answer spans) are written by fluent
Japanese speakers, including natives and non-natives. Annotators were given a
context and asked to generate non-trivial questions about information in the
context. ### Personal and Sensitive Information


No personal or sensitive information is included in this dataset. Dataset
annotators has been manually verified it.


Considerations for Using the Data
---------------------------------


Users should consider that the articles are sampled from Wikipedia articles but
not representative of all Wikipedia articles. ### Social Impact of Dataset


The social biases of this dataset have not yet been investigated. ### Discussion of Biases


The social biases of this dataset have not yet been investigated. Articles and
questions have been selected for quality and diversity. ### Other Known Limitations


The JaQuAD dataset has limitations as follows:


* Most of them are short answers.
* Assume that a question is answerable using the corresponding context.


This dataset is incomplete yet. If you find any errors in JaQuAD, please contact
us.


Additional Information
---------------------- ### Dataset Curators


Skelter Labs: URL ### Licensing Information


The JaQuAD dataset is licensed under the CC BY-SA 3.0 license. ### Acknowledgements


This work was supported by TPU Research Cloud (TRC) program.
For training models, we used cloud TPUs provided by TRC. We also thank
annotators who generated JaQuAD.
TAGS
#task_categories-question-answering #task_ids-extractive-qa #annotations_creators-crowdsourced #language_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Japanese #license-cc-by-sa-3.0 #arxiv-2202.01764 #region-us 
 ### Dataset Summary


Japanese Question Answering Dataset (JaQuAD), released in 2022, is a
human-annotated dataset created for Japanese Machine Reading Comprehension.
JaQuAD is developed to provide a SQuAD-like QA dataset in Japanese.
JaQuAD contains 39,696 question-answer pairs.
Questions and answers are manually curated by human annotators.
Contexts are collected from Japanese Wikipedia articles.
Fine-tuning BERT-Japanese
on JaQuAD achieves 78.92% for an F1 score and 63.38% for an exact match. ### Supported Tasks


* 'extractive-qa': This dataset is intended to be used for 'extractive-qa'. ### Languages


Japanese ('ja')


Dataset Structure
----------------- ### Data Instances


* Size of dataset files: 24.6 MB
* Size of the generated dataset: 48.6 MB
* Total amount of disk used: 73.2 MB


An example of 'validation': ### Data Fields


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'question\_type': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature.
	+ 'answer\_type': a 'string' feature. ### Data Splitting


JaQuAD consists of three sets, 'train', 'validation', and 'test'. They were
created from disjoint sets of Wikipedia articles. The 'test' set is not publicly
released yet. The following table shows statistics for each set.



Dataset Creation
---------------- ### Curation Rationale


The JaQuAD dataset was created by Skelter Labs to
provide a SQuAD-like QA dataset in Japanese. Questions are original and based
on Japanese Wikipedia articles. ### Source Data


The articles used for the contexts are from Japanese Wikipedia.
88.7% of articles are from the curated list of Japanese high-quality Wikipedia
articles, e.g., featured articles
and good articles. ### Annotations


Wikipedia articles were scrapped and divided into one more multiple paragraphs
as contexts. Annotations (questions and answer spans) are written by fluent
Japanese speakers, including natives and non-natives. Annotators were given a
context and asked to generate non-trivial questions about information in the
context. ### Personal and Sensitive Information


No personal or sensitive information is included in this dataset. Dataset
annotators has been manually verified it.


Considerations for Using the Data
---------------------------------


Users should consider that the articles are sampled from Wikipedia articles but
not representative of all Wikipedia articles. ### Social Impact of Dataset


The social biases of this dataset have not yet been investigated. ### Discussion of Biases


The social biases of this dataset have not yet been investigated. Articles and
questions have been selected for quality and diversity. ### Other Known Limitations


The JaQuAD dataset has limitations as follows:


* Most of them are short answers.
* Assume that a question is answerable using the corresponding context.


This dataset is incomplete yet. If you find any errors in JaQuAD, please contact
us.


Additional Information
---------------------- ### Dataset Curators


Skelter Labs: URL ### Licensing Information


The JaQuAD dataset is licensed under the CC BY-SA 3.0 license. ### Acknowledgements


This work was supported by TPU Research Cloud (TRC) program.
For training models, we used cloud TPUs provided by TRC. We also thank
annotators who generated JaQuAD.
passage: TAGS
#task_categories-question-answering #task_ids-extractive-qa #annotations_creators-crowdsourced #language_creators-crowdsourced #language_creators-found #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-Japanese #license-cc-by-sa-3.0 #arxiv-2202.01764 #region-us 
### Dataset Summary


Japanese Question Answering Dataset (JaQuAD), released in 2022, is a
human-annotated dataset created for Japanese Machine Reading Comprehension.
JaQuAD is developed to provide a SQuAD-like QA dataset in Japanese.
JaQuAD contains 39,696 question-answer pairs.
Questions and answers are manually curated by human annotators.
Contexts are collected from Japanese Wikipedia articles.
Fine-tuning BERT-Japanese
on JaQuAD achieves 78.92% for an F1 score and 63.38% for an exact match.### Supported Tasks


* 'extractive-qa': This dataset is intended to be used for 'extractive-qa'.### Languages


Japanese ('ja')


Dataset Structure
-----------------### Data Instances


* Size of dataset files: 24.6 MB
* Size of the generated dataset: 48.6 MB
* Total amount of disk used: 73.2 MB


An example of 'validation':### Data Fields


* 'id': a 'string' feature.
* 'title': a 'string' feature.
* 'context': a 'string' feature.
* 'question': a 'string' feature.
* 'question\_type': a 'string' feature.
* 'answers': a dictionary feature containing:
	+ 'text': a 'string' feature.
	+ 'answer\_start': a 'int32' feature.
	+ 'answer\_type': a 'string' feature.