Zero-shot transfer for implicit discourse relation classification
Murathan Kurfalı, Robert Östling · 2019
Automatically classifying the relation between sentences in a discourse is a challenging task, in particular when there is no overt expression of the relation.It becomes even more challenging by the fact that annotated training data exists only for a small number of languages, such as English and Chinese.We present a new system using zero-shot transfer learning for implicit discourse relation classification, where the only resource used for the target language is unannotated parallel text.This system is evaluated on the discourse-annotated TED-MDB parallel corpus, where it obtains good results for all seven languages using only English training data.