Chinese Dependency Parse Based Semantic Role Labeling
WANG Bukang,WANG Hongling,YUAN Xiaohong,ZHOU Guodong
School of Computer Science and Technology, Soochow University,Suzhou,Jiangsu 215006,China; Key Lab of Computer Information Processing Technology of Jiangsu Province,Suzhou,Jiangsu 215006,China
Abstract:Dependency representations are more simple and intuitive than constituent representations for Chinese parse. This paper implements a Chinese dependency parse based semantic role labeling (SRL) by using the similar methods in English SRL. In the system, effective pruning algorithm and useful features are adopted for Chinese dependency tree, and the semantic role identification and classification are accomplished by a maximum entropy classifier. Two different corpora are adopted to test our system, one is transferred from constituent-based corpus (CTB5.0), and the other is Chinese dataset provided by CoNLL 2009 shared task. Based on the two datasets, the system achieves, respectively, 84.30% and 81.68% in labeled F1 for gold predicates, and 81.02% and 81.33% for automatic predicates. Key wordscomputer application; Chinese information processing; Semantic Role Labeling;Dependency Relations;maximum entropy classifier
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