Papers with Chinese WSD
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. |