Open Domain Question Answering System Based on Knowledge Base

摘要：

　　Aiming at the task of open domain question answering based on knowledge base in NLP&CC 2016,we propose a SPE(subject predicate extraction)algorithm which can automatically extract a subjectpredicate pair from a simple question and translate it to a KB query.A novel method based on word vector similarity and predicate attention is used to score the candidate predicate after a simple topic entity linking method.Our approach achieved the F1-score of 82.47%on test data which obtained the first place in the contest of NLP&CC 2016 Shared Task 2(KBQA sub-task).Furthermore,there are also a series of experiments and comprehensive error analysis which can show the properties and defects of the new data set.

关键词： Chinese Natural language question answering Knowledge base Information extraction

作者: Yuxuan Lai Yang Lin Jiahao Chen Yansong Feng Dongyan Zhao

作者单位: School of Electronics Engineering and Computer Science,Peking University,Beijing,China School of Mathematical Sciences,Peking University,Beijing,China Institute of Computer Science & Technology,Peking University,Beijing,China

会议类型: 国际会议

会议名称: 第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)

会议地点: 昆明

会议语种:英文

页码: 1-12

在线出版日期: 2016-12-02（万方平台首次上网日期，不代表论文的发表时间）