Cross-lingual implicit discourse relation recognitionwith co-training

Abstract

A lack of labeled corpora obstructs the research progress on implicit discourse relation recognition (DRR) for Chinese, while there are some available discourse corpora in other languages, such as English. In this paper, we propose a cross-lingual implicit DRR framework that exploits an available English corpus for the Chinese DRR task. We use machine translation to generate Chinese instances from a labeled English discourse corpus. In this way, each instance has two independent views: Chinese and English views. Then we train two classifiers in Chinese and English in a co-training way, which exploits unlabeled Chinese data to implement better implicit DRR for Chinese. Experimental results demonstrate the effectiveness of our method.

Keywords

Cross-lingual / Implicit discourse relation recognition / Co-training

RIGHTS & PERMISSIONS

2018 Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature