Generating referring expressions in context: the GREC shared task evaluation challenges

Anja Belz, Eric Kow, Jette Viethen, Albert Gatt

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNChapter

Abstract

Until recently, referring expression generation (reg) research focused on the task of selecting the semantic content of definite mentions of listener-familiar discourse entities. In the grec research programme we have been interested in a version of the reg problem definition that is (i) grounded within discourse context, (ii) embedded within an application context, and (iii) informed by naturally occurring data. This paper provides an overview of our aims and motivations in this research programme, the data resources we have built, and the first three shared-task challenges, grec-msr’08, grec-msr’09 and grec-neg’09, we have run based on the data.
Original languageEnglish
Title of host publicationEmpirical Methods in Natural Language Generation
EditorsE. Krahmer, M. Theune
Place of PublicationBerlin
PublisherSpringer
Pages294-327
Number of pages34
Volume5790
ISBN (Print)9783642155727
Publication statusPublished - 1 Jan 2010

Publication series

NameLecture notes in computer science

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    Belz, A., Kow, E., Viethen, J., & Gatt, A. (2010). Generating referring expressions in context: the GREC shared task evaluation challenges. In E. Krahmer, & M. Theune (Eds.), Empirical Methods in Natural Language Generation (Vol. 5790, pp. 294-327). (Lecture notes in computer science). Springer.