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Discourse Coherence in the Wild: A Dataset, Evaluation and Methods

2018-05-14WS 2018Code Available0· sign in to hype

Alice Lai, Joel Tetreault

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Abstract

To date there has been very little work on assessing discourse coherence methods on real-world data. To address this, we present a new corpus of real-world texts (GCDC) as well as the first large-scale evaluation of leading discourse coherence algorithms. We show that neural models, including two that we introduce here (SentAvg and ParSeq), tend to perform best. We analyze these performance differences and discuss patterns we observed in low coherence texts in four domains.

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