关键词: 自然语言处理, 语义解析, 词对齐模型

Abstract: Semantic parsing is the task of transforming natural-language sentences into complete, formal, symbolic Meaning Representations （MR） suitable for reasoning or machine-understanding. In recent years, the research of semantic parsing in English has made great progress. However, little work has been done in Chinese semantic parsing. There are inherent differences between Chinese and English, therefore one cannot simply apply methods, which are feasible for English, to Chinese. This paper proposes a statistical approach called WACSP aiming at Chinese semantic parsing, which considers the process of converting Chinese sentence into its corresponding meaning as a machine translation procedure. At first, it turns the frequently-used dataset GEOQUERY into Chinese dataset, in which each data contains a Chinese sentence and its accurate meaning. Then it uses the word alignment model to acquire the bilingual dictionary made up by the Chinese natural language string and its meaning. In the end, it determines the ultimate semantic analysis by learning a statistical model. Experimental results show that WACSP performs well with higher precision and coverage.

Key words: natural language processing, semantic parsing, word alignment model