The Annotation Guideline of LST20 Corpus
Not on the map. Why?
Abstract (arXiv)
This report presents the annotation guideline for LST20, a large-scale corpus with multiple layers of linguistic annotation for Thai language processing. Our guideline consists of five layers of linguistic annotation: word segmentation, POS tagging, named entities, clause boundaries, and sentence boundaries. The dataset complies to the CoNLL-2003-style format for ease of use. LST20 Corpus offers five layers of linguistic annotation as aforementioned. At a large scale, it consists of 3,164,864 words, 288,020 named entities, 248,962 clauses, and 74,180 sentences, while it is annotated with 16 distinct POS tags. All 3,745 documents are also annotated with 15 news genres. Regarding its sheer size, this dataset is considered large enough for developing joint neural models for NLP. With the existence of this publicly available corpus, Thai has become a linguistically rich language for the first time.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Aug 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2023PyThaiNLP: Thai Natural Language Processing in Pythoncited by 27
- 2021WangchanBERTa: Pretraining transformer-based Thai Language Modelscited by 25
- 2023PhayaThaiBERT: Enhancing a Pretrained Thai Language Model with Unassimilated Loanwordscited by 2
- 2026ThaiTrees: Thai Syntactic Dependency Trees Across Domainscited by 0
- 2026ThaiTrees: Thai Syntactic Dependency Trees Across Domains23 Sep 2026
- 2023PyThaiNLP: Thai Natural Language Processing in Python7 Dec 2023
- 2023PhayaThaiBERT: Enhancing a Pretrained Thai Language Model with Unassimilated Loanwords21 Nov 2023
- 2021WangchanBERTa: Pretraining transformer-based Thai Language Models24 Jan 2021