Is It That Difficult to Find a Good Preference Order for the Incremental Algorithm?

Authors


should be sent to Emiel Krahmer, Tilburg Center for Cognition and Communication (TiCC), School of Humanities, Tilburg University, P.O. Box 90153, NL-5000 LE, Tilburg, The Netherlands. E-mail: e.j.krahmer@uvt.nl.

Abstract

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.

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