Abstract
Recent research has enabled important progress in developing agents aimed at real-world linguistic interaction with humans. Hence, within the general shift of research focus from “information” to “knowledge”, an important question is how to apply large-scale knowledge resources in order to improve agents’ capabilities of linguistic interaction with humans. This paper presents research toward an efficient representation of the necessary perceptual knowledge in dialogue with a particular focus on reference expressions. We generalize an existing formal model of reference expressions involving perceptual grouping in order to account for a number of types of reference expressions that the previous model could not account for. Our model yields an increase in both coverage and accuracy of referent identification − which has been confirmed in preliminary experiments. We outline an algorithm for the future application of this model to other languages, showing how the model can be extended to deal with large-scale multi-language input data.
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Spanger, P., Tokunaga, T. (2008). On the Representation of Perceptual Knowledge for Understanding Reference Expressions. In: Tokunaga, T., Ortega, A. (eds) Large-Scale Knowledge Resources. Construction and Application. LKR 2008. Lecture Notes in Computer Science(), vol 4938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78159-2_25
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DOI: https://doi.org/10.1007/978-3-540-78159-2_25
Publisher Name: Springer, Berlin, Heidelberg
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