ThaiCoref: Thai Coreference Resolution Dataset

Pontakorn Trakuekul, Wei Qi Leong, Charin Polpanumas, Jitkapat Sawatphol, William Chandra Tjhi +1 more
6/10/2024
cs.CL

No official code found. Best implementation: nlp-chula/thai-coref (8 stars, last commit 2026-01-13).

Abstract

While coreference resolution is a well-established research area in Natural Language Processing (NLP), research focusing on Thai language remains limited due to the lack of large annotated corpora. In this work, we introduce ThaiCoref, a dataset for Thai coreference resolution. Our dataset comprises 777,271 tokens, 44,082 mentions and 10,429 entities across four text genres: university essays, newspapers, speeches, and Wikipedia. Our annotation scheme is built upon the OntoNotes benchmark with adjustments to address Thai-specific phenomena. Utilizing ThaiCoref, we train models employing a multilingual encoder and cross-lingual transfer techniques, achieving a best F1 score of 67.88\% on the test set. Error analysis reveals challenges posed by Thai's unique linguistic features. To benefit the NLP community, we make the dataset and the model publicly available at http://www.github.com/nlp-chula/thai-coref .

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Code Implementations(1)

nlp-chula/thai-corefCommunity100%

Coreference Resolution Dataset and Models for Thai Language

81Jan 22, 20249 months ago

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Cite this paper

@article{trakuekul2024thaicoref,
  title  = {ThaiCoref: Thai Coreference Resolution Dataset},
  author = {Pontakorn Trakuekul and Wei Qi Leong and Charin Polpanumas and Jitkapat Sawatphol and William Chandra Tjhi and Attapol T. Rutherford},
  year   = {2024},
  eprint = {2406.06000},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.06000v1}
}

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