Papers with Chinese WSD

3 papers
Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation (2021.findings-emnlp)

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Challenge: Word sense disambiguation (WSD) methods have not explored word-formations in parataxis languages like Chinese.
Approach: They propose to leverage word-formation knowledge to enhance Chinese WSD by incorporating word-forms into sense disambiguation models.
Outcome: The proposed model improves on baselines in Chinese word sense disambiguation (WSD) with word-formation knowledge, the results show.
LTRS: Improving Word Sense Disambiguation via Learning to Rank Senses (2025.coling-main)

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Challenge: Conventional training strategies only consider predefined senses for target words and learn each of them from relatively limited instances, neglecting the influence of similar ones.
Approach: They propose a method to rank senses to improve the task of word Sense Disambiguation (WSD) by ranking an expanded list of sense definitions.
Outcome: The proposed method achieves a SOTA F1 score of 79.6% in Chinese WSD and shows faster convergence than previous methods.
Try to Substitute: An Unsupervised Chinese Word Sense Disambiguation Method Based on HowNet (2020.coling-main)

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Challenge: Existing unsupervised methods for word sense disambiguation cannot work for HowNet-based WSD because of its uniqueness.
Approach: They propose a method which exploits the masked language model task of pre-trained language models to conduct word sense disambiguation using a lexical knowledge base as the sense inventory.
Outcome: The proposed method achieves significantly better performance than baseline methods.

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