Deep enhanced representation for implicit discourse relation recognition

作     者：Bai, Hongxiao Zhao, Hai 

作者机构：Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2018年

核心收录：

主　　题：Character recognition 

摘      要：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 stateof- the-art accuracy with greater than 48% in 11-way and F1score greater than 50% in 4-way classifications for the first time according to our best knowledge. Copyright © 2018, The Authors. All rights reserved.