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We argue that semantic meanings of a sentence or clause can not beinterpreted independently from the rest of a paragraph, or independently fromall discourse relations and the overall paragraph-level discourse structure.With the goal of improving implicit discourse relation classification, weintroduce a paragraph-level neural networks that model inter-dependenciesbetween discourse units as well as discourse relation continuity and patterns,and predict a sequence of discourse relations in a paragraph. Experimentalresults show that our model outperforms the previous state-of-the-art systemson the benchmark corpus of PDTB.

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