Disambiguate Chinese Word Sense Based on Linguistics Knowledge

Word sense disambiguation (WSD) is important to many application problems in natural language processing fields, such as machine translation, parsing analysis and information retrieval. In this paper, we propose a new method to determine correct sense categories of Chinese words based on linguistics knowledge. The left word string and the right word string around the ambiguous word are respectively analyzed. Their syntactic structures are obtained for determining its intended sense. Syntactic category and part of speech are extracted as disambiguation features. A naive bayesian model is used as the classifier. Experimental results showed that the accuracy rate of classification arrives at 64%. The performance of disambiguation is improved.