Error-driven learning with bracketing constraints

被引：0
|
作者：
Miyata, Takashi
Hasida, Koiti
机构：
来源：
FINITE-STATE METHODS AND NATURAL LANGUAGE PROCESSING | 2006年 / 4002卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A chunking algorithm with a Markov model is extended to accept bracketing constraints. The extended algorithm is implemented by modifying a state-of-the-art Japanese dependency parser. Then the effect of bracketing constraints in preventing parsing errors is evaluated. A method for improving the parser's accuracy is proposed. That method adds brackets according to a set of optimal brackets obtained from a training corpus. Although the method's coverage is limited, the F-measure for the sentences to which the method adds brackets is improved by about 7%.
引用
收藏
页码：144 / 155
页数：12
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