Generating referring expressions: boolean extensions of the incremental algorithm
Computational Linguistics
Graph-based generation of referring expressions
Computational Linguistics
PCFG models of linguistic tree representations
Computational Linguistics
Generating referring expressions involving relations
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Group-based generation of referring expressions
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
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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.