A New Ranking Method for Chinese Discourse Tree Building
Wan Fuqiang, Xueqiang Lv, Yunfang Wu, XU Yi-feng · 2015
This paper proposes a novel method for sentence-level Chinese discourse tree building. The authors constrcut a Chinese discourse annotated corpus in the framework of Rhetorical Structure Theory, and propose a ranking-like SVM (SVM-R) model to automatically build the tree structure, which can capture the relative associated strength among three consecutive text spans rather than only two adjacent spans as most previous approaches do. The experimental results show that proposed SVM-R method significantly outperforms the state-of-the-art in discourse parsing accuracy. It is also demonstrated that the useful features for discourse tree building are consistent with Chinese language characteristics.