Focus-sensitive relation disambiguation for implicit discourse relation detection  

作　　者：Yu HONG Siyuan DING Yang XU Xiaoxia JIANG Yu WANG Jianmin YAO Qiaoming ZHU Guodong ZHOU 

机构地区：[1]Natural Language Processing Lab,School of Computer Science&Technology,Soochow University,Suzhou 215006,China [2]Science and Technology on Information Systems Engineering Laboratory,Nanjing 210007,China

出　　处：《Frontiers of Computer Science》2019年第6期1266-1281,共16页中国计算机科学前沿（英文版）

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.61672368,61373097,61672367,61331011);the Research Foundation of the Ministry of Education and China Mobile(MCM20150602);Natural Science Foundation of Jiangsu(BK20151222).

摘　　要：We study implicit discourse relation detection,which is one of the most challenging tasks in the field of discourse analysis.We specialize in ambiguous implicit discourse relation,which is an imperceptible linguistic phenomenon and therefore difficult to identify and eliminate.In this paper,we first create a novel task named implicit discourse relation disambiguation(IDRD).Second,we propose a focus-sensitive relation disambiguation model that affirms a truly-correct relation when it is triggered by focal sentence constituents.In addition,we specifically develop a topicdriven focus identification method and a relation search system(RSS)to support the relation disambiguation.Finally,we improve current relation detection systems by using the disambiguation model.Experiments on the penn discourse treebank(PDTB)show promising improvements.

关 键 词：Implicit discourse relation focus-sensitive implicit relation disambiguation topic-driven focus identification 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]