Abstract:
Aiming at the bottlenecks of syntactic tree-based Semantic Role Labeling(SRL), this paper explores dependency relationship-based semantic role labeling. By properly integrating dependency parsing, predicate identification, feature extraction, semantic role identification and semantic role classification, this system achieves the F1 measure of 80.94% on the WSJ portion of the CoNLL2008 SRL Shared Task, using automatic dependency parsing. Experimental results show that it is better than the F1 measure of syntactic tree-based semantic role labeling apparently.
Key words:
Semantic Role Labeling(SRL),
dependency parsing,
dependency relationship
摘要: 针对以句法成分为基本标注单元语义角色标注的瓶颈问题,描述一个以依存关系为标注单元的语义角色标注系统,经过依存关系分析、谓词标识、特征抽取、角色识别和角色分类,最终在CoNLL2008 SRL Shared Task自动依存分析的WSJ测试集取得了较好的结果,F1值达到了80.94%,结果证明其性能明显好于基于句法分析的SRL。
关键词:
语义角色标注,
依存分析,
依存关系
CLC Number:
WANG Hong-lin; WANG Hong-ling; ZHOU Guo-dong. Semantic Role Labeling Based on Dependency Relationship[J]. Computer Engineering, 2009, 35(15): 82-84.
汪红林;王红玲;周国栋. 基于依存关系的语义角色标注[J]. 计算机工程, 2009, 35(15): 82-84.