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Focus-sensitive relation disambiguation for implicit discourse relation detection
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作者 Yu HONG Siyuan DING +5 位作者 Yang XU Xiaoxia JIANG Yu WANG Jianmin YAO Qiaoming ZHU Guodong ZHOU 《Frontiers of Computer Science》 SCIE EI CSCD 2019年第6期1266-1281,共16页
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 ... 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. 展开更多
关键词 Implicit discourse relation focus-sensitive implicit relation disambiguation topic-driven focus identification
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