{"type":"ScholarlyArticle","title":"Neural Discourse Segmentation","authors":[{"name":"Jing Li","slug":"jing-li","given":"Jing","family":"Li","affiliation":"Inception Institute of Artificial Intelligence , Abu Dhabi , United Arab Emirates"}],"abstract":"Identifying discourse structures and coherence relations in a piece of text is a fundamental task in natural language processing. The first step of this process is segmenting sentences into clause-like units called elementary discourse units (EDUs). Traditional solutions to discourse segmentation heavily rely on carefully designed features. In this demonstration, we present SegBot, a system to split a given piece of text into sequence of EDUs by using an end-to-end neural segmentation model. Our model does not require hand-crafted features or external knowledge except word embeddings, yet it outperforms state-of-the-art solutions to discourse segmentation.","doi":"10.24963/ijcai.2019/949","url":"https://ijcai.org/proceedings/2019/949","pdf":"https://ijcai.org/proceedings/2019/0949.pdf","markdown":"https://ijcai.org/proceedings/2019/949.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/949","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Demos","track":"Demos","number":949,"pages":{"first":6539,"last":6541},"keywords":["AI: Machine Learning","AI: Natural Language Processing"],"videos":[],"references":[{"position":1,"raw":"[Carlson et al., 2002] Lynn Carlson, Mary Ellen Okurowski, and Daniel Marcu. 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