The reviewed record of science sign in
Pith

arxiv: 2406.06000 · v1 · pith:AQSY4CN3 · submitted 2024-06-10 · cs.CL

ThaiCoref: Thai Coreference Resolution Dataset

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:AQSY4CN3record.jsonopen to challenge →

classification cs.CL
keywords datasetthaicoreferenceresolutionthaicoreflanguageresearchachieving
0
0 comments X
read the original 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 .

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.