Papers › Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation
Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation
Hua Zheng, Lei LI, Damai Dai, Deli Chen, Tianyu Liu, Xu sun, Yang Liu
In parataxis languages like Chinese, word meanings are constructed using specific word-formations, which can help to disambiguate word senses. However, such knowledge is rarely explored in previous word sense disambiguation (WSD) methods. In this paper, we propose to leverage word-formation knowledge to enhance Chinese WSD. We first construct a large-scale Chinese lexical sample WSD dataset with word-formations. Then, we propose a model FormBERT to explicitly incorporate word-formations into sense disambiguation. To further enhance generalizability, we design a word-formation predictor module in case word-formation annotations are unavailable. Experimental results show that our method brings substantial performance improvement over strong baselines.
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