Is it that difficult to find a good preference order for the incremental algorithm?

Emiel Krahmer, Ruud Koolen, Mariet Theune

    Research output: Contribution to journalArticleAcademicpeer-review

    6 Citations (Scopus)
    22 Downloads (Pure)


    In a recent article published in this journal (van Deemter, Gatt, van der Sluis, & Power, 2012), the authors criticize the Incremental Algorithm (a well-known algorithm for the generation of referring expressions due to Dale & Reiter, 1995, also in this journal) because of its strong reliance on a pre-determined, domain-dependent Preference Order. The authors argue that there are potentially many different Preference Orders that could be considered, while often no evidence is available to determine which is a good one. In this brief note, however, we suggest (based on a learning curve experiment) that finding a Preference Order for a new domain may not be so difficult after all, as long as one has access to a handful of human-produced descriptions collected in a semantically transparent way. We argue that this is due to the fact that it is both more important and less difficult to get a good ordering of the head than of the tail of a Preference Order.
    Original languageUndefined
    Pages (from-to)837-841
    Number of pages5
    JournalCognitive science
    Issue number5
    Publication statusPublished - Jul 2012


    • EWI-22511
    • IR-83409
    • METIS-296140

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