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.
基金
the National Natural Science Foundation of China (No.60435020, 60575042 and 60503072).
关键词
动词
细分
自然语言加工
句法分析
Verb subdivision
Maximum entropy model
Syntactic parsing
Natural language processing
