基於組合特徵的漢語名詞詞義消歧

A Study on Noun Sense Disambiguation Based on Syntagmatic Features

Word sense disambiguation (WSD) plays an important role in many areas of natural language processing, such as machine translation, information retrieval, sentence analysis, and speech recognition. Research on WSD has great theoretical and practical significance. The main purposes of this study were to study the kind of knowledge that is useful for WSD, and to establish a new WSD model based on syntagmatic features, which can be used to disambiguate noun sense in Mandarin Chinese effectively. Close correlation has been found between lexical meaning and its distribution. According to a study in the field of cognitive science [Choueka, 1983], people often disambiguate word sense using only a few other words in a given context (frequently only one additional word). Thus, the relationships between one word and others can be effectively used to resolve ambiguity. Based on a descriptive study of more than 4,000 Chinese noun senses, a multi-level framework of syntagmatic analysis was designed to describe the syntactic and semantic constraints of Chinese nouns. All of these polyseme nouns were surveyed, and it was found that different senses have different and complementary distributions at the syntax and/or collocation levels. This served as a foundation for establishing an WSD model by using grammatical information and a thesaurus provided by linguists.