关键词: 句法分析, 中心子节点过滤表, 短语结构, 依存结构, 树库

Abstract: Dependency parsing is a key part of the natural language processing. Currently, there are some researches on Vietnamese phrase structure trees, but few on dependency structure treebank. This paper proposes a novel method, which combines the Vietnamese language features and grammatical features, uses the head percolation table as well as statistical machining learning method to convert the Vietnamese phrase structure treebank into a dependency one. Firstly, according to Chinese dependency annotation system and Vietnamese grammar rules, a list of dependencies are developed; Secondly, integrating the characteristics of Vietnamese language, the head percolation table is worked out; Thirdly, using the head percolation table to carry out preliminary conversion; Finally, using dependency tagger to tag dependency. Vietnamese dependency structure treebank increases by training converted treebank with MSTParser tool. The precision of conversion reaches 89.4%. The experimental results show that the proposed method gives a better solution of converting constituent-to-dependency treebank for Vietnamese.

Key words: syntactic analysis, head percolation table, phrase structure, dependency structure, treebank