Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/22377
Title: Generating referring expressions in context : the GREC task evaluation challenges
Other Titles: Empirical methods in natural language generation : data-oriented methods and empirical evaluation
Authors: Belz, Anja
Kow, Eric
Viethen, Jette
Gatt, Albert
Keywords: Natural language processing (Computer science)
Corpora (Linguistics)
Linguistic analysis (Linguistics)
Reference (Linguistics)
Issue Date: 2010
Publisher: Springer-Verlag Berlin Heidelberg
Citation: Belz, A., Kow, E., Viethen, J., & Gatt, A. (2010). Generating referring expressions in context: the GREC task evaluation challenges. In E. Krahmer, & M. Theune (Eds.), Empirical methods in natural language generation: data-oriented methods and empirical evaluation (pp. 294-327). Heidelberg: Springer-Verlag Berlin Heidelberg.
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 ap- plication 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.
URI: https://www.um.edu.mt/library/oar//handle/123456789/22377
ISBN: 9783642155727
Appears in Collections:Scholarly Works - InsLin

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