Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph

Zeyu Dai, Ruihong Huang
2018 Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)  
We argue that semantic meanings of a sentence or clause can not be interpreted independently from the rest of a paragraph, or independently from all discourse relations and the overall paragraph-level discourse structure. With the goal of improving implicit discourse relation classification, we introduce a paragraph-level neural networks that model inter-dependencies between discourse units as well as discourse relation continuity and patterns, and predict a sequence of discourse relations in a
more » ... paragraph. Experimental results show that our model outperforms the previous state-of-the-art systems on the benchmark corpus of PDTB.
doi:10.18653/v1/n18-1013 dblp:conf/naacl/DaiH18 fatcat:bgltndzrfzdjjcz2glxepp47pi