ThaiCoref: Thai Coreference Resolution Dataset
<|reference_start|>ThaiCoref: Thai Coreference Resolution Dataset: 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 .<|reference_end|>
@article{trakuekul2024thaicoref:,
    title={ThaiCoref: Thai Coreference Resolution Dataset},
    author={Pontakorn Trakuekul, Wei Qi Leong, Charin Polpanumas, Jitkapat
  Sawatphol, William Chandra Tjhi, Attapol T. Rutherford},
    journal={arXiv preprint arXiv:2406.06000},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.06000},
    primaryClass={cs.CL}
}