SUBDIVIDING VERBS TO IMPROVE SYNTACTIC PARSING

被引：3

作者：

Liu Ting Ma Jinshan Zhang Huipeng Li Sheng Information Retrieval LabHarbin Institute of TechnologyHarbin China ^{[150001
]}

机构：

来源：

JournalofElectronics(China) | 2007年 / 03期

关键词：

Verb subdivision; Maximum entropy model; Syntactic parsing; Natural language process-ing;

D O I：

暂无

中图分类号：

TP391.1 [文字信息处理];

学科分类号：

081203 ; 0835 ;

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.

引用

页码：347 / 352

页数：6