The challenging issues of discourse relation recognition in Chinese are addressed. Due to the lack of Chinese discourse corpora, we construct a moderate corpus with humanannotated discourse relations. Based on the corpus, a statistical classifier is proposed, and various features are explored in the experiments. The experimental results show that our method achieves an accuracy of 88.28% and an F-Score of 63.69% in four-class classification and achieves an F-Score of 93.57% in the best case.
REF constructed a Chinese discourse corpus with 81 articles.
Chinese Discourse Relation Recognition
IJCNLP
Computer Science