Year: 2019
Type: conference-paper
Abstract: 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.
DOI: 10.18653/v1/w19-5927
Authors: Murathan Kurfalı, Robert Östling
Institution: Stockholm University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2966639296