Improving Chinese Semantic Role Labeling with English Proposition Bank

摘要：

　　Most researches to SRL focus on English.It is still a challenge to improve the SRL performance of other language.In this paper,we introduce a two-pass approach to do Chinese SRL with a Recurrent Neural Network(RNN)model.We use English Proposition Bank(EPB)to improve the performance of Chinese SRL.Experimental result shows a significant improvement over the state-of-the-art methods on Chinese Proposition Bank(CPB),which reaches 78.39%F1 score.

关键词： Chinese semantic role labeling two-pass approach Recurrent Neural Network English resource

作者: Tianshi Li Qi Li BaoBao Chang

作者单位: Key Laboratory of Computational Linguistics,Ministry of Education,School of Electronics Engineering Collaborative Innovation Center for Language Ability,Xuzhou 221009,China

会议类型: 国内会议

会议名称: 第十五届全国计算语言学学术会议(CCL2016)暨第四届基于自然标注大数据的自然语言处理国际学术研讨会(NLP-NABD-2016)

会议地点: 烟台

会议语种:英文

页码: 1-9

在线出版日期: 2016-10-14（万方平台首次上网日期，不代表论文的发表时间）