| Abstract | 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 differences in discourse organization between Chinese and English, including differences in information 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 resulting
semi-supervised system reaches state-of-art performance on the task of discourse relation
detection, and outperforms a supervised system on discourse relation classification. |
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