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arXiv · 1804.05918

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

Zeyu Dai·Ruihong Huang
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Abstract

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 paragraph. Experimental results show that our model outperforms the previous state-of-the-art systems on the benchmark corpus of PDTB.

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Zeyu Dai, Ruihong Huang. 2018-04-16. Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph. https://arxiv.org/abs/1804.05918

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