Referring expression generation: what can we learn from human data?

Jette Viethen, Robert Dale

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

Abstract

In this paper, we reflect on what we can learn about the processes involved in the generation of referring expressions by looking at a corpus of human-produced data. We find that the data vastly underspecifies what might be involved algorithmically, but it does rule out a number of popular algorithms for referring expression generation as candidates for models of what people do. We posit an alternative algorithmic schema which forces us to focus more clearly on the questions that need to be answered experimentally if we are to develop algorithms that emulate human behaviour on this task.
Original languageEnglish
Title of host publicationPre-Cogsci 2009
Subtitle of host publicationProduction of referring expressions : bridging the gap between computational and empirical approaches to reference. Workshop program & proceedings
Place of PublicationAmsterdam
PublisherNetherlands Organization for Scientific Research
Pages1-6
Number of pages6
Publication statusPublished - 2009
EventPre-Cogsci 2009 : Production of referring expressions : bridging the gap between computational and empirical approaches to reference - Amsterdam, The Netherlands
Duration: 29 Jul 200929 Jul 2009

Conference

ConferencePre-Cogsci 2009 : Production of referring expressions : bridging the gap between computational and empirical approaches to reference
CityAmsterdam, The Netherlands
Period29/07/0929/07/09

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