Capturing acceptable variation in distinguishing descriptions

Jette Viethen*, Robert Dale

*Corresponding author for this work

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

1 Citation (Scopus)


Almost all existing referring expression generation algorithms aim to find one best referring expression for a given intended referent. However, human-produced data demonstrates that, for any given entity, many perfectly acceptable referring expressions exist. At the same time, it is not the case that all logically possible descriptions are acceptable; so, if we remove the requirement to produce only one best solution, how do we avoid generating undesirable descriptions? Our aim in this paper is to sketch a framework that allows us to capture constraints on referring expression generation, so that the set of logically possible descriptions can be reduced to just those that are acceptable.

Original languageEnglish
Title of host publicationProceedings of the 11th European Workshop on Natural Language Generation, ENLG 07
EditorsStephan Busemann
Place of PublicationGermany
PublisherDFKI GmbH
Number of pages8
Publication statusPublished - 2007
Event11th European Workshop on Natural Language Generation, ENLG 07 - Schloss Dagstuhl, Germany
Duration: 17 Jun 200720 Jun 2007


Other11th European Workshop on Natural Language Generation, ENLG 07
CitySchloss Dagstuhl


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