
# Dataset Card for `iapp_wiki_qa_squad`

## 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/iapp-technology/iapp-wiki-qa-dataset
- **Repository:** https://github.com/iapp-technology/iapp-wiki-qa-dataset
- **Paper:**
- **Leaderboard:**
- **Point of Contact:** https://github.com/iapp-technology/iapp-wiki-qa-dataset

### Dataset Summary

`iapp_wiki_qa_squad` is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from [the original iapp-wiki-qa-dataset](https://github.com/iapp-technology/iapp-wiki-qa-dataset) to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, resulting in 5761/742/739 questions from 1529/191/192 articles.

### Supported Tasks and Leaderboards

extractive question answering

### Languages

Thai

## Dataset Structure

### Data Instances

An example from the dataset:
```
{'article_id': '0U2lA8nJQESIxbZrjZQc',
'question_id': '0U2lA8nJQESIxbZrjZQc_000',
'context': 'นายสุวัฒน์ วรรณศิริกุล (1 พฤศจิกายน พ.ศ. 2476 - 31 กรกฎาคม พ.ศ. 2555) อดีตรองหัวหน้าพรรคพลังประชาชน อดีตประธานสมาชิกสภาผู้แทนราษฎร และประธานภาคกรุงเทพมหานคร พรรคพลังประชาชน อดีตสมาชิกสภาผู้แทนราษฎรกรุงเทพมหานครหลายสมัย ได้รับการเลือกตั้งเป็นสมาชิกสภาผู้แทนราษฎรครั้งแรกในปี พ.ศ. 2529 ในสังกัดพรรคประชากรไทย และสังกัดพรรคพลังประชาชน เป็นพรรคสุดท้าย',
'question': 'สุวัฒน์ วรรณศิริกุล เกิดวันที่เท่าไร',
'answers': {'text': ['1 พฤศจิกายน พ.ศ. 2476'],
 'answer_start': [24],
 'answer_end': [45]},
'title': 'สุวัฒน์ วรรณศิริกุล',
'created_by': 'gmnjGRF0y0g7QRZDd9Qgz3AgiHJ3',
'created_on': '2019-08-18 05:05:51.358000+00:00',
'is_pay': {'date': None, 'status': False}}
{'article_id': '01KZTrxgvC5mOovXFMPJ',
'question_id': '01KZTrxgvC5mOovXFMPJ_000',
'context': 'พัทธ์ธีรา ศรุติพงศ์โภคิน (เกิด 3 ธันวาคม พ.ศ. 2533) หรือชื่อเล่นว่า อร เป็นนักแสดงหญิงชาวไทย สำเร็จมัธยมศึกษาจากCatholic Cathedral College ประเทศนิวซีแลนด์ และปริญญาตรีจากRaffles International College สาขา Business Marketing\n\nเข้าสู่วงการตั้งแต่อายุ 6 ขวบ จากการแสดงละครเวทีกับ ครูชลประคัลภ์ จันทร์เรือง จากนั้นก็เล่นโฆษณาในวัยเด็ก 2- 3 ชิ้น และยังเคยแสดงช่วงละครสั้น ในรายการซุปเปอร์จิ๋ว ประมาณปี 2542\n\nปัจจุบันเป็นทั้ง นักแสดง , พิธีกร และ วีเจ อยู่ที่คลื่น เก็ท 102.5 Bangkok International Hits Music Station และยังเป็นพิธีกรให้กับช่อง ทรู มิวสิก',
'question': 'พัทธ์ธีรา ศรุติพงศ์โภคิน เกิดวันที่เท่าไร',
'answers': {'text': ['3 ธันวาคม พ.ศ. 2533'],
 'answer_start': [31],
 'answer_end': [50]},
'title': 'พัทธ์ธีรา ศรุติพงศ์โภคิน',
'created_by': 'gmnjGRF0y0g7QRZDd9Qgz3AgiHJ3',
'created_on': '2019-08-07 14:00:38.778000+00:00',
'is_pay': {'status': True,
 'total': 2.5,
 'date': '2019-08-13 10:47:28.095000+00:00'}}
```

### Data Fields

```
{
    "question_id": question id
    "article_id": article id
    "title": article title
    "context": article texts
    "question": question
    "answers":
        {
            "text": answer text
            "answer_start": answer beginning position
            "answer_end": answer exclusive upper bound position
        }
    ),
}
```

### Data Splits

|             | train | valid | test |
|-------------|-------|-------|------|
| # questions | 5761  | 742   | 739  |
| # articles  | 1529  | 191   | 192  |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

From the original `iapp-wiki-qa-dataset`, [@cstorm125](https://github.com/cstorm125/) applied the following processing:

- Select questions with one, non-empty answer
- Select questions whose answers match `textDetection` fields
- Select questions whose answers are 100-character long or shorter
- 80/10/10 train-validation-split at article level

#### Who are the source language producers?

Wikipedia authors for contexts and annotators hired by [iApp](https://iapp.co.th/) for questions and answer annotations

### Annotations

#### Annotation process

Annotators hired by [iApp](https://iapp.co.th/) are asked create questions and answers for each article.

#### Who are the annotators?

Annotators hired by [iApp](https://iapp.co.th/)

### 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

[More Information Needed]

## Additional Information

### Dataset Curators

Original dataset by [iApp](https://iapp.co.th/). SQuAD formattting by [PyThaiNLP](https://github.com/PyThaiNLP/).

### Licensing Information

MIT

### Citation Information

```
@dataset{kobkrit_viriyayudhakorn_2021_4539916,
  author       = {Kobkrit Viriyayudhakorn and
                  Charin Polpanumas},
  title        = {iapp\_wiki\_qa\_squad},
  month        = feb,
  year         = 2021,
  publisher    = {Zenodo},
  version      = 1,
  doi          = {10.5281/zenodo.4539916},
  url          = {https://doi.org/10.5281/zenodo.4539916}
}
```

### Contributions

Thanks to [@cstorm125](https://github.com/cstorm125) for adding this dataset.
task_categories:question-answering task_ids:extractive-qa task_ids:open-domain-qa annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:1K<n<10K source_datasets:extended|other-iapp-wiki-qa-dataset language:th license:mit region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["th"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["extended|other-iapp-wiki-qa-dataset"], "task_categories": ["question-answering"], "task_ids": ["extractive-qa", "open-domain-qa"], "pretty_name": "IappWikiQaSquad", "dataset_info": {"features": [{"name": "question_id", "dtype": "string"}, {"name": "article_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"}, {"name": "answer_end", "dtype": "int32"}]}], "config_name": "iapp_wiki_qa_squad", "splits": [{"name": "train", "num_bytes": 16107541, "num_examples": 5761}, {"name": "validation", "num_bytes": 2120768, "num_examples": 742}, {"name": "test", "num_bytes": 2032016, "num_examples": 739}], "download_size": 2876630, "dataset_size": 20260325}}
TAGS
#task_categories-question-answering #task_ids-extractive-qa #task_ids-open-domain-qa #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-iapp-wiki-qa-dataset #language-Thai #license-mit #region-us 

Dataset Card for 'iapp\_wiki\_qa\_squad'
========================================


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


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks and Leaderboards
	+ 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
	+ Contributions


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


* Homepage: URL
* Repository: URL
* Paper:
* Leaderboard:
* Point of Contact: URL


### Dataset Summary


'iapp\_wiki\_qa\_squad' is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from the original iapp-wiki-qa-dataset to SQuAD format, resulting in 5761/742/739 questions from 1529/191/192 articles.


### Supported Tasks and Leaderboards


extractive question answering


### Languages


Thai


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


### Data Instances


An example from the dataset:


### Data Fields


### Data Splits



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


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


From the original 'iapp-wiki-qa-dataset', @cstorm125 applied the following processing:


* Select questions with one, non-empty answer
* Select questions whose answers match 'textDetection' fields
* Select questions whose answers are 100-character long or shorter
* 80/10/10 train-validation-split at article level


#### Who are the source language producers?


Wikipedia authors for contexts and annotators hired by iApp for questions and answer annotations


### Annotations


#### Annotation process


Annotators hired by iApp are asked create questions and answers for each article.


#### Who are the annotators?


Annotators hired by iApp


### 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


### Other Known Limitations


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


### Dataset Curators


Original dataset by iApp. SQuAD formattting by PyThaiNLP.


### Licensing Information


MIT


### Contributions


Thanks to @cstorm125 for adding this dataset.



### Dataset Summary


'iapp\_wiki\_qa\_squad' is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from the original iapp-wiki-qa-dataset to SQuAD format, resulting in 5761/742/739 questions from 1529/191/192 articles. ### Supported Tasks and Leaderboards


extractive question answering ### Languages


Thai


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


An example from the dataset: ### Data Fields ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization


From the original 'iapp-wiki-qa-dataset', @cstorm125 applied the following processing:


* Select questions with one, non-empty answer
* Select questions whose answers match 'textDetection' fields
* Select questions whose answers are 100-character long or shorter
* 80/10/10 train-validation-split at article level #### Who are the source language producers?


Wikipedia authors for contexts and annotators hired by iApp for questions and answer annotations ### Annotations #### Annotation process


Annotators hired by iApp are asked create questions and answers for each article. #### Who are the annotators?


Annotators hired by iApp ### 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 ### Other Known Limitations


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


Original dataset by iApp. SQuAD formattting by PyThaiNLP. ### Licensing Information


MIT ### Contributions


Thanks to @cstorm125 for adding this dataset.
TAGS
#task_categories-question-answering #task_ids-extractive-qa #task_ids-open-domain-qa #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-iapp-wiki-qa-dataset #language-Thai #license-mit #region-us 
 ### Dataset Summary


'iapp\_wiki\_qa\_squad' is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from the original iapp-wiki-qa-dataset to SQuAD format, resulting in 5761/742/739 questions from 1529/191/192 articles. ### Supported Tasks and Leaderboards


extractive question answering ### Languages


Thai


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


An example from the dataset: ### Data Fields ### Data Splits



Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization


From the original 'iapp-wiki-qa-dataset', @cstorm125 applied the following processing:


* Select questions with one, non-empty answer
* Select questions whose answers match 'textDetection' fields
* Select questions whose answers are 100-character long or shorter
* 80/10/10 train-validation-split at article level #### Who are the source language producers?


Wikipedia authors for contexts and annotators hired by iApp for questions and answer annotations ### Annotations #### Annotation process


Annotators hired by iApp are asked create questions and answers for each article. #### Who are the annotators?


Annotators hired by iApp ### 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 ### Other Known Limitations


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


Original dataset by iApp. SQuAD formattting by PyThaiNLP. ### Licensing Information


MIT ### Contributions


Thanks to @cstorm125 for adding this dataset.
passage: TAGS
#task_categories-question-answering #task_ids-extractive-qa #task_ids-open-domain-qa #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-iapp-wiki-qa-dataset #language-Thai #license-mit #region-us 
### Dataset Summary


'iapp\_wiki\_qa\_squad' is an extractive question answering dataset from Thai Wikipedia articles. It is adapted from the original iapp-wiki-qa-dataset to SQuAD format, resulting in 5761/742/739 questions from 1529/191/192 articles.### Supported Tasks and Leaderboards


extractive question answering### Languages


Thai


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


An example from the dataset:### Data Fields### Data Splits



Dataset Creation
----------------### Curation Rationale### Source Data#### Initial Data Collection and Normalization


From the original 'iapp-wiki-qa-dataset', @cstorm125 applied the following processing:


* Select questions with one, non-empty answer
* Select questions whose answers match 'textDetection' fields
* Select questions whose answers are 100-character long or shorter
* 80/10/10 train-validation-split at article level#### Who are the source language producers?


Wikipedia authors for contexts and annotators hired by iApp for questions and answer annotations### Annotations#### Annotation process


Annotators hired by iApp are asked create questions and answers for each article.#### Who are the annotators?


Annotators hired by iApp### 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### Other Known Limitations


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