Neural Networks in Chinese Lexical Classification

Lexical attributes, like syntactic (part-of-speech) and semantic (semantic category) attributes, are in most cases, ambiguous in every languages. Automatic resolution of ambiguity of these attributes can be achieved using different techniques; rule-based, statistical, NN-based and their hybrids. Moreover, one linguistic feature also has influence over the resolution of ambiguity of another feature; eg.. knowledge of syntactical category can assist smooth disambiguation of semantic category and vice versa. Properly disambiguated syntactic and semantic properties of lexicon may significantly help us in word sense disambiguation, text analysis, information retreival, natural language understanding and speech processing etc. In this paper, we have presented our neural network based Classification Tool. We have used this tool in Part-of-Speech tagging and SemanticCategory tagging of Chinese lexicon with the help of thesaurus and large training corpus. Experimental results are analysed and compared.