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---
license: odc-by
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
- name: source
dtype: string
- name: metadata
struct:
- name: Filename
dtype: string
- name: author
dtype: string
- name: channel_name
dtype: string
- name: domain
dtype: string
- name: is_subtitle_generated
dtype: string
- name: license
dtype: string
- name: provenance
dtype: string
- name: revid
dtype: string
- name: src
dtype: string
- name: ticker
dtype: string
- name: title
dtype: string
- name: url
dtype: string
- name: year
dtype: float64
splits:
- name: train
num_bytes: 8513541142
num_examples: 397488
- name: validation
num_bytes: 83508453
num_examples: 4044
download_size: 2639043294
dataset_size: 8597049595
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
task_categories:
- fill-mask
- text-generation
language:
- th
tags:
- legal
- finance
- medical
pretty_name: Magostreen
size_categories:
- 1M<n<10M
---
We have collected additional Thai text that is unlikely to be included in the common crawl from various sources. The total number of documents collected is as follows:425,304 documents, we deduplication these noncc documents to later divide them into train sets for further web data and validation set.
The following table shows the analysis of the data after deduplication.
| type | Source | Number of documents | Number of words | Cultural? | Human-craft? | Evaluation topics? |
|----------------------|------------------------------------------------------------|---------------------|-----------------|:---------:|:------------:|:-----------------------------:|
| encyclopedic | th.wikibooks.org | 1,179 | 756,175 | No | | Common safety |
| | th.wikipedia.org | 162,189 | 74,151,797 | No | | Common safety |
| | th.wikiquote.org | 929 | 156,910 | No | | Common safety |
| | th.wikisource.org | 1,890 | 5,601,908 | No | | Common safety |
| finance | airesearch/cmdf_vistec | 86,813 | 348,189,390 | No | | Common safety |
| government document | lift catalog data | 1 | 6,931 | No | Yes/No | Common safety |
| | data.go.th | 9,488 | 2,766,950 | No | No | Common safety |
| | envilink.go.th | 1 | 10,659 | | | |
| | government data catalog smart plus | 427 | 5,290,950 | Yes | Yes/No | Common safety/ Cross-lingual |
| | https://ratchakitcha.soc.go.th | 59,744 | 175,031,218 | Yes | Yes | Culture safety/ Cross-lingual |
| | nakhoratchasima data catalog | 1 | 68,000 | Yes | Yes | Country safety/ Cross-lingual |
| | opdc data portal | 3,148 | 598,829 | | | |
| | open-d | 7 | 284,100 | | | |
| | royal thai government | 1 | 41,356 | | | |
| | National Economic and Social Development Board | 1 | 37,663 | | | |
| | pythainlp/thailand-policy-statements | 60 | 226,087 | | | |
| legal | pythainlp/thai-cc-license | 6 | 50,727 | | | |
| | pythainlp/thai-constitution-corpus | 20 | 444,313 | | | |
| | pythainlp/thailaw-v1.0 | 52,317 | 79,715,118 | | | |
| academic literature | government data catalog smart plus | 427 | 5,290,950 | | | |
| | openbase.in.th | 4,173 | 165,909,425 | | | |
| | platform for social empowerment and transformation | 90 | 209,716 | | | |
| | pythainlp/thai-it-books | 7 | 174,644 | | | |
| | pythainlp/thai-tnhc2-books | 353 | 22,002,703 | | | |
| | pythainlp/tlcv2.0_oa | 361 | 2,970,463 | | | |
| | TDRI | 25 | 2,801,106 | | | |
| | Bangkok Open Data | 10 | 2,334 | | | |
| | Open educational resources repository | 14 | 47,951 | | | |
| | CMU Journal of Law and Social Sciences | 47 | 37,976 | | | |
| | E-journal of education studies, Burapha University | 68 | 59,137 | | | |
| | Chulalongkorn University Law Journal | 64 | 46,425 | | | |
| | Lanna Journal of Health Promotion and Environmental Health | 53 | 52,320 | | | |
| | Journal of Educational Studies, Burapha University | 64 | 56,320 | | | |
| | Journal of Yanasangwon Research Institute | 65 | 47,286 | | | |
| | Journal of Food and Drug Administration | 79 | 115,541 | | | |
| | https://github.com/kongruksiamza/ebook-for-education | 8 | 83,432 | | | |
| | social technology institute | 3 | 11,152 | | | |
| youtube | youtube | 17,826 | 46,613,632 | | | |
Documents from some sources cannot be directly used or easily processed. It is necessary to use text extraction technology (OCR) to extract the text due to the document format in PDF. The table below shows the number and proportion of documents that required OCR.
| Source | Number of documents | Number of documents required for PCR | Percentage of documents requiring OCR |
|--------------------------------------:|--------------------:|-------------------------------------:|--------------------------------------:|
| data.go.th | 9488 | 18 | 0.189713 |
| government data catalog smart plus | 427 | 198 | 46.370023 |
| ebook construction | 8 | 8 | 100 |
| openbase.in.th | 4173 | 3443 | 82.50659 |
| opendata.nesdc.go.th | 7 | 3 | 42.857143 |
| royal thai government | 1 | 1 | 100 |
| Open educational resources repository | 14 | 2 | 14.285714 |
The model used for text extraction ishttps://github.com/VikParuchuri/marker
In the future, you should try VLM, such as:https://olmocr.allenai.org/Or Typhoon2 Vision
Data from various sources can be classified into 6 types as shown in the table below.
| Domain | count | proportion |
|-------------:|-------:|-----------:|
| Encyclopedic | 166187 | 41.34 |
| Finance | 86813 | 21.59 |
| Government | 72,879 | 18.13 |
| Legal | 52,343 | 13.02 |
| YouTube | 17,837 | 4.43 |
| Education | 5,911 | 1.47 |
The additional documents we collect are confirmed to be open source and have a license to allow for redistribution, with the copyright share as shown in the table below.
| license | count | proportion |
|----------------:|-------:|-----------:|
| CC BY-SA 4.0 | 166187 | 41.388233 |
| CC0 | 112871 | 28.110088 |
| CC BY 4.0 | 112407 | 27.994531 |
| CC BY-NC-SA 4.0 | 4173 | 1.03927 |
| ODC-BY | 3769 | 0.938655 |
| CC BY-NC 4.0 | 1853 | 0.461483 |
| CC BY-NC-ND 4.0 | 250 | 0.062262 |
| CC BY 3.0 | 13 | 0.003238 |
| GFDL | 6 | 0.001494 |
| OGL | 3 | 0.000747 |
Resources
- Pre-training data (web): https://huggingface.co/datasets/aisingapore/WangchanLION-Web
- Pre-training data (curated): https://huggingface.co/datasets/aisingapore/WangchanLION-Curated
- Pre-training model: https://huggingface.co/aisingapore/WangchanLION-v3
- SFT model: https://huggingface.co/aisingapore/WangchanLION-v3-IT
- Paper: https://arxiv.org/abs/2507.14664
- Blog: https://sea-lion.ai/sea-lion-wangchanlionv3/
- Github: https://github.com/vistec-AI/Mangosteen |