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  1. Kees van Deemter, Albert Gatt, Ielka van der Sluis & Richard Power (2012). Assessing the Incremental Algorithm: A Response to Krahmer Et Al. Cognitive Science 36 (5):842-845.
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  2. Kees van Deemter, Albert Gatt, Ielka van der Sluis & Richard Power (2012). Generation of Referring Expressions: Assessing the Incremental Algorithm. Cognitive Science 36 (5):799-836.
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  3. Kees van Deemter, Albert Gatt, Ielka van der Sluis & Richard Power (2012). Assessing the Incremental Algorithm: A Response to Krahmer Et Al. Cognitive Science 36 (5):842-845.
    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., non-semantically-balanced) corpora.
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  4. Kees van Deemter, Albert Gatt, Roger P. G. van Gompel & Emiel Krahmer (2012). Toward a Computational Psycholinguistics of Reference Production. Topics in Cognitive Science 4 (2):166-183.
    This article introduces the topic ‘‘Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference’’ of the journal Topics in Cognitive Science. We argue that computational and psycholinguistic approaches to reference production can benefit from closer interaction, and that this is likely to result in the construction of algorithms that differ markedly from the ones currently known in the computational literature. We focus particularly on determinism, the feature of existing algorithms that is perhaps most clearly at (...)
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  5. Kees van Deemter, Albert Gatt, Ielka van der Sluis & Richard Power (2011). Generation of Referring Expressions: Assessing the Incremental Algorithm. Cognitive Science 36 (5):799-836.
    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 test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out that (...)
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  6. Albert Gatt & Kees van Deemter (2007). Lexical Choice and Conceptual Perspective in the Generation of Plural Referring Expressions. Journal of Logic, Language and Information 16 (4):423-443.
    A fundamental part of the process of referring to an entity is to categorise it (for instance, as the woman). Where multiple categorisations exist, this implicitly involves the adoption of a conceptual perspective. A challenge for the automatic Generation of Referring Expressions is to identify a set of referents coherently, adopting the same conceptual perspective. We describe and evaluate an algorithm to achieve this. The design of the algorithm is motivated by the results of psycholinguistic experiments.
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