An efficient augmented-context-free parsing algorithm
Computational Linguistics
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Glr*: a robust grammar-focused parser for spontaneously spoken language
Glr*: a robust grammar-focused parser for spontaneously spoken language
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This paper presents an extended GLR parsing algorithm with grammar PCFG* that is based on Tomita's GLR parsing algorithm and extends it further. We also define a new grammar---PCFG* that is based on PCFG and assigns not only probability but also frequency associated with each rule. So our syntactic parsing system is implemented based on rule-based approach and statistics approach. Furthermore our experiments are executed in two fields: Chinese base noun phrase identification and full syntactic parsing. And the results of these two fields are compared from three ways. The experiments prove that the extended GLR parsing algorithm with PCFG* is an efficient parsing method and a straightforward way to combine statistical property with rules. The experiment results of these two fields are presented in this paper.