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Krahmer, Emiel; Koolen, Ruud; Theune, Mariet – Cognitive Science, 2012
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.…
Descriptors: Natural Language Processing, Mathematics, Computational Linguistics
van Deemter, Kees; Gatt, Albert; van der Sluis, Ielka; Power, Richard – Cognitive Science, 2012
A substantial amount of recent work in natural language generation has focused on the generation of "one-shot" referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We…
Descriptors: Natural Language Processing, Mathematics, Computational Linguistics
van Deemter, Kees; Gatt, Albert; van der Sluis, Ielka; Power, Richard – Cognitive Science, 2012
This response discusses the experiment reported in Krahmer et al.'s Letter to the Editor of "Cognitive Science". We observe that their results do not tell us whether the Incremental Algorithm is better or worse than its competitors, and we speculate about implications for reference in complex domains, and for learning from "normal" (i.e.,…
Descriptors: Experiments, Natural Language Processing, Mathematics, Computational Linguistics