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.
@article{arxiv.1907.12885,
title = {Zero-shot transfer for implicit discourse relation classification},
author = {Murathan Kurfalı and Robert Östling},
journal= {arXiv preprint arXiv:1907.12885},
year = {2019}
}