Collective Entity Linking on Relational Graph Model with Mentions

摘要：

　　Given a source document with extracted mentions,entity linking callsfor map-ping the mention to an entity in reference knowledge base.Previous en-tity linking approaches mainly focus on generic statistic features to link mentions independently.However,additional interdependence among mentions in the same document achieved from relational analysis can improve the accuracy.This paper propose a collective entity linking model which effectively leverages the global interdependence among mentions in the same source document.The model unifies semantic relations and co-reference relations into relational infer-ence for se-mantic information extraction.Graph based linking algorithm is uti-lized to ensure per mention with only one candidate entity.Experiments on da-tasets show the proposed model significantly out-performs the state-of-the-art re-latedness approaches in term of accuracy.

关键词： Collective Entity Linking Entity Disambiguation Relational Graph

作者: Jing Gong Chong Feng Yong Liu Ge Shi Heyan Huang

作者单位: Beijing Institute of Technology University,Beijing 100081,China State Key Lab,,Beijing 100081,China

会议类型: 国内会议

会议名称: 第十六届全国计算语言学学术会议暨第五届基于自然标注大数据的自然语言处理国际学术研讨会

会议地点: 南京

会议语种:英文

页码: 1-12

在线出版日期: 2017-10-13（万方平台首次上网日期，不代表论文的发表时间）