Cross-lingual implicit discourse relation recognition with co-training
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.
关键词：
Cross-lingual,
Implicit discourse relation recognition,
Co-training
