Cross-lingual and cross-domain discourse segmentation of entire documents

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Discourse segmentation is a crucial step in building end-to-end discourse parsers. However, discourse segmenters only exist for a few languages and domains. Typically they only detect intra-sentential segment boundaries, assuming gold standard sentence and token segmentation, and relying on high-quality syntactic parses and rich heuristics that are not generally available across languages and domains. In this paper, we propose statistical discourse segmenters for five languages and three domains that do not rely on gold pre-annotations. We also consider the problem of learning discourse segmenters when no labeled data is available for a language. Our fully supervised system obtains 89.5% F1 for English newswire, with slight drops in performance on other domains, and we report supervised and unsupervised (cross-lingual) results for five languages in total.

Original languageEnglish
Title of host publicationProceedings of the 55th Annual Meeting of the Association for Computational Linguistics : Short papers
Number of pages7
Volume2
PublisherAssociation for Computational Linguistics
Publication date1 Jan 2017
Pages237-243
ISBN (Electronic)9781945626760
DOIs
Publication statusPublished - 1 Jan 2017
Event55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada
Duration: 30 Jul 20174 Aug 2017

Conference

Conference55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
LandCanada
ByVancouver
Periode30/07/201704/08/2017
SponsorAmazon, Apple, Baidu, et al, Google, Tencent

ID: 195013952