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.
|Title of host publication||Empirical Methods in Natural Language Generation|
|Editors||E. Krahmer, M. Theune|
|Place of Publication||Berlin|
|Number of pages||34|
|Publication status||Published - 1 Jan 2010|
|Name||Lecture notes in computer science|
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.