Chinese Hedge Scope Detection Based on Structure and Semantic Information

摘要：

　　Hedge detection aims to distinguish factual and uncertain information,which is important in information extraction.The task of hedge detection contains two subtasks: identifying hedge cues and detecting their linguistic scopes.Hedge scope detection is dependent on syntactic and semantic information.Previous researches usually use lexical and syntactic information and ignore deep semantic information.This paper proposes a novel syntactic and se-mantic information exploitation method for scope detection.Composite kernel model is employed to capture lexical and syntactic information.Long short-term memory(LSTM)model is adopted to explore semantic information.Furthermore,we exploit a hybrid system to integrate composite kernel and LSTM model into a unified framework.Experiments on the Chinese Biomedical Hedge Information(CBHI)corpus show that composite kernel model could effectively capture lexical and syntactic information,LSTM model could capture deep semantic information and their combination could further improve the performance of hedge scope detection.

关键词： hedge scope detection structure information semantic information

作者: Huiwei Zhou Junli Xu Yunlong Yang Huijie Deng Long Chen Degen Huang

作者单位: School of Computer Science and Technology,Dalian University of Technology,Dalian 116024,Liaoning,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: 1-12

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）