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Deep Enhanced Representation for Implicit Discourse Relation Recognition

2018-07-13COLING 2018Code Available0· sign in to hype

Hongxiao Bai, Hai Zhao

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Abstract

Implicit discourse relation recognition is a challenging task as the relation prediction without explicit connectives in discourse parsing needs understanding of text spans and cannot be easily derived from surface features from the input sentence pairs. Thus, properly representing the text is very crucial to this task. In this paper, we propose a model augmented with different grained text representations, including character, subword, word, sentence, and sentence pair levels. The proposed deeper model is evaluated on the benchmark treebank and achieves state-of-the-art accuracy with greater than 48% in 11-way and F_1 score greater than 50% in 4-way classifications for the first time according to our best knowledge.

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