基于句式与句模对应规则的语义角色标注

大规模语义角色标注语料库的构建可以为计算机理解自然语言的语义提供有用的训练数据。该文主要研究服务于语义角色标注语料库构建的语义角色标注规则。在人工语义角色标注的基础上,分析句式和句模的对应关系,并总结出一套基于句式的语义角色标注规则,在测试集上达到78.73%的正确率。基于上述规则,可以在构建语义角色标注语料库时完成自动标注的工作,标注人员在此基础上进行人工校对,可有效地减少工作量。

Semantic Role Labeling Based on Correspondence Rules Between Syntactic Pattern and Semantic Pattern of Sentences

The construction of large-scale semantic corpus can provide useful training data for computer to understand the semantics of natural language. This paper focuses on the semantic rules for the construction of semantic corpus. On the basis of artificial semantic role tagging, the corresponding relation between syntactic patterns and semantic patterns of sentences is analyzed, and a set of semantic role labeling rules based on sentence patterns is extracted, leading to 78.73% precision on the test set.