关键词: 结构化支持向量机, 上下文无关文法, 结构上下文相关, 中文句法分析

Abstract: Syntactic parsing is a basic technology of natural language understanding, and it is the cornerstone of deep language understanding. At present, the parsing method is based on the hypothesis of context free grammar. In fact, the context has a strong correlation in phrase structure trees. If the structural information can be used, it can further improve the accuracy of the parser. This paper combines the multiple structural information in syntactic structure trees, the structural information (such as father node or left and right sister nodes) in the non-terminal node can strengthen grammar rules of context constraints. And then this paper uses the method of structural support vector machines (SSVMs) for Chinese parsing. The experimental results show that the method of multiple structural information fusion can resolve the structural ambiguity and improve the accuracy and F1 value.

Key words: structural support vector machines, context-free grammar, structure context correlation, Chinese parsing