Generating referring expressions in context: the GREC task evaluation challenges

Anja Belz; Eric Kow; Jette Viethen; Albert Gatt

doi:10.1007/978-3-642-15573-4_15

Generating referring expressions in context: the GREC task evaluation challenges

Anja Belz^*, Eric Kow, Jette Viethen, Albert Gatt

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

33 Citations (Scopus)

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 language	English
Title of host publication	Empirical methods in natural language generation
Subtitle of host publication	data-oriented methods and empirical evaluation
Editors	Emiel Krahmer, Mariët Theune
Place of Publication	Berlin; New York
Publisher	Springer, Springer Nature
Pages	294-327
Number of pages	34
ISBN (Electronic)	9783642155734
ISBN (Print)	9783642155727
DOIs	https://doi.org/10.1007/978-3-642-15573-4_15
Publication status	Published - 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5790 LNAI
ISSN (Print)	03029743
ISSN (Electronic)	16113349

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10.1007/978-3-642-15573-4_15

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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). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5790 LNAI). Springer, Springer Nature. https://doi.org/10.1007/978-3-642-15573-4_15

Belz, Anja ; Kow, Eric ; Viethen, Jette et al. / Generating referring expressions in context : the GREC task evaluation challenges. Empirical methods in natural language generation: data-oriented methods and empirical evaluation. editor / Emiel Krahmer ; Mariët Theune. Berlin; New York : Springer, Springer Nature, 2010. pp. 294-327 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5790 LNAI, Springer, Springer Nature, Berlin; New York, pp. 294-327. https://doi.org/10.1007/978-3-642-15573-4_15

Generating referring expressions in context: the GREC task evaluation challenges. / Belz, Anja; Kow, Eric; Viethen, Jette et al.
Empirical methods in natural language generation: data-oriented methods and empirical evaluation. ed. / Emiel Krahmer; Mariët Theune. Berlin; New York: Springer, Springer Nature, 2010. p. 294-327 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5790 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Kow, Eric

AU - Viethen, Jette

AU - Gatt, Albert

PY - 2010

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N2 - 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.

AB - 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.

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DO - 10.1007/978-3-642-15573-4_15

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SN - 9783642155727

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Empirical methods in natural language generation

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Belz A, Kow E, Viethen J, Gatt A. Generating referring expressions in context: the GREC task evaluation challenges. In Krahmer E, Theune M, editors, Empirical methods in natural language generation: data-oriented methods and empirical evaluation. Berlin; New York: Springer, Springer Nature. 2010. p. 294-327. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-15573-4_15

Generating referring expressions in context: the GREC task evaluation challenges

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