Referring expression generation through attribute-based heuristics

Robert Dale*, Jette Viethen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

34 Citations (Scopus)

Abstract

In this paper, we explore a corpus of human-produced referring expressions to see to what extent we can learn the referential behaviour the corpus represents. Despite a wide variation in the way subjects refer across a set of ten stimuli, we demonstrate that component elements of the referring expression generation process appear to generalise across participants to a significant degree. This leads us to propose an alternative way of thinking of referring expression generation, where each attribute in a description is provided by a separate heuristic.

Original languageEnglish
Title of host publicationProceedings of the 12th European Workshop on Natural Language Generation, ENLG 2009
Place of PublicationUnited States
PublisherAssociation for Computational Linguistics (ACL)
Pages58-65
Number of pages8
Publication statusPublished - 2009
Event12th European Workshop on Natural Language Generation, ENLG 2009 - Athens, Greece
Duration: 30 Mar 20093 Apr 2009

Other

Other12th European Workshop on Natural Language Generation, ENLG 2009
CountryGreece
CityAthens
Period30/03/093/04/09

Fingerprint Dive into the research topics of 'Referring expression generation through attribute-based heuristics'. Together they form a unique fingerprint.

Cite this