Disambiguate Words like Composing Them: A Morphology-Informed Approach to Enhance Chinese Word Sense Disambiguation

Yue Wang, Qiliang Liang, Yaqi Yin, Hansi Wang, Yang Liu

Abstract
In parataxis languages like Chinese, word meanings are highly correlated with morphological knowledge, which can help to disambiguate word senses. However, in-depth exploration of morphological knowledge in previous word sense disambiguation (WSD) methods is still lacking due to the absence of publicly available resources. In this paper, we are motivated to enhance Chinese WSD with full morphological knowledge, including both word-formations and morphemes. We first construct the largest and releasable Chinese WSD resources, including the lexico-semantic inventories MorInv and WrdInv, a Chinese WSD dataset MiCLS, and an out-of-volcabulary (OOV) test set. Then, we propose a model, MorBERT, to fully leverage this morphology-informed knowledge for Chinese WSD and achieve a SOTA F1 of 92.18% in the task. Finally, we demonstrated the model’s robustness in low-resource settings and generalizability to OOV senses. These resources and methods may bring new insights into and solutions for various downstream tasks in both computational and humanistic fields.
Anthology ID:
2024.acl-long.819
Volume:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
15354–15365
Language:
URL:
https://aclanthology.org/2024.acl-long.819
DOI:
10.18653/v1/2024.acl-long.819
Bibkey:
Cite (ACL):
Yue Wang, Qiliang Liang, Yaqi Yin, Hansi Wang, and Yang Liu. 2024. Disambiguate Words like Composing Them: A Morphology-Informed Approach to Enhance Chinese Word Sense Disambiguation. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 15354–15365, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Disambiguate Words like Composing Them: A Morphology-Informed Approach to Enhance Chinese Word Sense Disambiguation (Wang et al., ACL 2024)
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