SUBDIVIDING VERBS TO IMPROVE SYNTACTIC PARSING  

作　　者：Liu Ting Ma Jinshan Zhang Huipeng Li Sheng 

机构地区：[1]Information Retrieval Lab, Harbin Institute of Technology, Harbin 150001, China

出　　处：《Journal of Electronics(China)》2007年第3期347-352,共6页电子科学学刊（英文版）

基　　金：the National Natural Science Foundation of China (No.60435020, 60575042 and 60503072).

摘　　要：This paper proposes a new way to improve the performance of dependency parser: subdividing verbs according to their grammatical functions and integrating the information of verb subclasses into lexicalized parsing model. Firstly,the scheme of verb subdivision is described. Secondly,a maximum entropy model is presented to distinguish verb subclasses. Finally,a statistical parser is developed to evaluate the verb subdivision. Experimental results indicate that the use of verb subclasses has a good influence on parsing performance.This paper proposes a new way to improve the performance of dependency parser： subdividing verbs according to their grammatical functions and integrating the information of verb subclasses into lexicalized parsing model. Firstly, the scheme of verb subdivision is described. Secondly, a maximum entropy model is presented to distinguish verb subclasses. Finally, a statistical parser is developed to evaluate the verb subdivision. Experimental results indicate that the use of verb subclasses has a good influence on parsing performance.

关 键 词：Verb subdivision Maximum entropy model Syntactic parsing Natural language processing 

分 类 号：TN912.3[电子电信—通信与信息系统]