Datasets:
best2009

	---
	annotations_creators:
	- expert-generated
	language_creators:
	- found
	languages:
	- th
	licenses:
	- cc-by-nc-sa-3-0
	multilinguality:
	- monolingual
	size_categories:
	- 100k<n<1M
	source_datasets:
	- original
	task_categories:
	- structure-prediction
	task_ids:
	- structure-prediction-other-word-tokenization
	---

	# Dataset Card for `best2009`

	## 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 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)

	## Dataset Description

	- Homepage: https://aiforthai.in.th/
	- Repository: https://aiforthai.in.th/corpus.php
	- Paper:
	- Leaderboard:
	- Point of Contact: https://aiforthai.in.th/

	### Dataset Summary

	`best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by [NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for [BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10). The test set answers are not provided publicly.

	### Supported Tasks and Leaderboards

	word tokenization

	### Languages

	Thai

	## Dataset Structure

	### Data Instances

	```
	{'char': ['?', 'ภ', 'ู', 'ม', 'ิ', 'ป', 'ั', 'ญ', 'ญ', 'า', 'ช', 'า', 'ว', 'บ', '้', 'า', 'น', '\n'], 'char_type': [4, 1, 10, 1, 10, 1, 4, 1, 1, 10, 1, 10, 1, 1, 9, 10, 1, 4], 'fname': 'encyclopedia_00031.txt', 'is_beginning': [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1]}
	{'char': ['ภ', 'ู', 'ม', 'ิ', 'ป', 'ั', 'ญ', 'ญ', 'า', 'ช', 'า', 'ว', 'บ', '้', 'า', 'น', ' ', 'ห', 'ม', 'า', 'ย', 'ถ', 'ึ', 'ง', ' ', 'ค', 'ว', 'า', 'ม', 'ร', 'ู', '้', 'ข', 'อ', 'ง', 'ช', 'า', 'ว', 'บ', '้', 'า', 'น', ' ', 'ซ', 'ึ', '่', 'ง', 'เ', 'ร', 'ี', 'ย', 'น', 'ร', 'ู', '้', 'ม', 'า', 'จ', 'า', 'ก', 'พ', '่', 'อ', 'แ', 'ม', '่', ' ', 'ป', 'ู', '่', 'ย', '่', 'า', 'ต', 'า', 'ย', 'า', 'ย', ' ', 'ญ', 'า', 'ต', 'ิ', 'พ', 'ี', '่', 'น', '้', 'อ', 'ง', ' ', 'ห', 'ร', 'ื', 'อ', 'ผ', 'ู', '้', 'ม', 'ี', 'ค', 'ว', 'า', 'ม', 'ร', 'ู', '้', 'ใ', 'น', 'ห', 'ม', 'ู', '่', 'บ', '้', 'า', 'น', 'ใ', 'น', 'ท', '้', 'อ', 'ง', 'ถ', 'ิ', '่', 'น', 'ต', '่', 'า', 'ง', 'ๆ', '\n'], 'char_type': [1, 10, 1, 10, 1, 4, 1, 1, 10, 1, 10, 1, 1, 9, 10, 1, 5, 3, 1, 10, 1, 1, 10, 1, 5, 1, 1, 10, 1, 1, 10, 9, 1, 1, 1, 1, 10, 1, 1, 9, 10, 1, 5, 1, 10, 9, 1, 11, 1, 10, 1, 1, 1, 10, 9, 1, 10, 1, 10, 1, 1, 9, 1, 11, 1, 9, 5, 1, 10, 9, 1, 9, 10, 1, 10, 1, 10, 1, 5, 1, 10, 1, 10, 1, 10, 9, 1, 9, 1, 1, 5, 3, 1, 10, 1, 3, 10, 9, 1, 10, 1, 1, 10, 1, 1, 10, 9, 11, 1, 3, 1, 10, 9, 1, 9, 10, 1, 11, 1, 1, 9, 1, 1, 1, 10, 9, 1, 1, 9, 10, 1, 7, 4], 'fname': 'encyclopedia_00031.txt', 'is_beginning': [1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1]}
	```

	### Data Fields

	- `fname`: file name; also marks if article is articles, news, encyclopedia or novels
	- `char`: characters
	- `char_type`: character types as adopted from []() by [deepcut](https://github.com/rkcosmos/deepcut)
	- `is_beginning`: is beginning of word

	### Data Splits

	\| \| train \| test \|
	\|-------------------------\|------------\|---------\|
	\| # lines \| 148,995 \| 2,252 \|
	\| avg words per line \| 39.05 \| NA \|
	\| total words \| 5,818,521 \| NA \|
	\| avg characters per line \| 140.39 \| 202.79 \|
	\| total characters \| 20,918,132 \| 456,684 \|
	\| # lines articles \| 16,990 \| NA \|
	\| # lines encyclopedia \| 50,631 \| NA \|
	\| # lines novels \| 50,140 \| NA \|
	\| # lines news \| 31,234 \| NA \|

	## Dataset Creation

	### Curation Rationale

	The dataset was created for [BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10) by [NECTEC](https://www.nectec.or.th/).

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	Respective authors of the articles, news, encyclopedia and novels

	### Annotations

	#### Annotation process

	Detailed annotation guidelines can be found in `BEST_Guideline_Release1.pdf` as part of the uncompressed files. Word tokenization standard used was [InterBEST2009](http://hltshare.fbk.eu/IWSLT2015/InterBEST2009Guidelines-2.pdf)

	#### Who are the annotators?

	[More Information Needed]

	### Personal and Sensitive Information

	All data are curated from public sources. No personal and sensitive information is expected to be included.

	## Considerations for Using the Data

	### Social Impact of Dataset

	- word tokenization dataset from articles, news, encyclopedia and novels

	### Discussion of Biases

	- texts are relatively formal ones from articles, news, encyclopedia and novels.
	- word tokenization standard used was [InterBEST2009](http://hltshare.fbk.eu/IWSLT2015/InterBEST2009Guidelines-2.pdf).

	### Other Known Limitations

	- some tags unrelated to word tokenization (`<NE>` and `<AB>`) are cleaned out.
	- no word boundary provdied for the test set

	## Additional Information

	### Dataset Curators

	[NECTEC](https://www.nectec.or.th/)

	### Licensing Information

	CC-BY-NC-SA 3.0

	### Citation Information

	Dataset:
	```
	@inproceedings{kosawat2009best,
	title={BEST 2009: Thai word segmentation software contest},
	author={Kosawat, Krit and Boriboon, Monthika and Chootrakool, Patcharika and Chotimongkol, Ananlada and Klaithin, Supon and Kongyoung, Sarawoot and Kriengket, Kanyanut and Phaholphinyo, Sitthaa and Purodakananda, Sumonmas and Thanakulwarapas, Tipraporn and others},
	booktitle={2009 Eighth International Symposium on Natural Language Processing},
	pages={83--88},
	year={2009},
	organization={IEEE}
	}
	@inproceedings{boriboon2009best,
	title={Best corpus development and analysis},
	author={Boriboon, Monthika and Kriengket, Kanyanut and Chootrakool, Patcharika and Phaholphinyo, Sitthaa and Purodakananda, Sumonmas and Thanakulwarapas, Tipraporn and Kosawat, Krit},
	booktitle={2009 International Conference on Asian Language Processing},
	pages={322--327},
	year={2009},
	organization={IEEE}
	}
	```

	Character type features:
	```
	@inproceedings{haruechaiyasak2009tlex,
	title={TLex: Thai lexeme analyser based on the conditional random fields},
	author={Haruechaiyasak, Choochart and Kongyoung, Sarawoot},
	booktitle={Proceedings of 8th International Symposium on Natural Language Processing},
	year={2009}
	}
	```