Cross-lingual Discourse Relation Analysis: A corpus study and a semi-supervised classification system

We present a cross-lingual discourse relation analysis based on a parallel corpus with discourse information available only for one language. First, we conduct a corpus study to explore dif-ferences in discourse organization between Chinese and English, including differences in infor-mation packaging, implicit/explicit discourse expression divergence, and discourse connective ambiguities. Second, we introduce a novel approach to learning to recognize discourse relations, using the parallel corpus instead of discourse annotation in the language of interest. Our result-ing semi-supervised system reaches state-of-art performance on the task of discourse relation detection, and outperforms a supervised system on discourse relation classification.