Abstract
The semantic content determination or attribute selection of definite descriptions is one of the most traditional tasks in natural language generation. Algorithms of this kind are required to produce descriptions that are brief (or even minimal) and, at the same time, as close as possible to the choices made by human speakers. In this work we attempt to achieve a balance between brevity and humanlikeness by implementing a number of algorithms for the task. The algorithms are tested against descriptions produced by humans in two different domains, suggesting a strategy that is both computationally simple and comparable to the state of the art in the field.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Dale, R., Reiter, E.: Computational interpretations of the Gricean maxims in the generation of referring expressions. Cognitive Science (19) (1995)
Grice, H.P.: Logic and Conversation. In: Cole, P., Morgan, J.L. (eds.) Syntax and Semantics. Speech Acts, vol. iii, pp. 41–58. Academic Press, New York (1975)
Dale, R.: Cooking up referring expressions. In: Proceedings of the 27th Annual Meeting of the Association for Computational Linguistics (1989)
Kelleher, J.D.: DIT - Frequency Based Incremental Attribute Selection for GRE. UCNLG+MT, pp. 90–91 (2007)
Gatt, A., van der Sluis, I., van Deemter, K.: Evaluating algorithms for the generation of referring expressions using a balanced corpus. In: Proceedings of the 11th European Workshop on Natural Language Generation, pp. 49–56 (2007)
van Deemter, K., van der Sluis, I., Gatt, A.: Building a semantically transparent corpus for the generation of referring expressions. In: INLG 2006 (2006)
Bohnet, B.: IS-FBN, IS-FBS, IS-IAC: The Adaptation of Two Classic Algorithms for the Generation of Referring Expressions in order to Produce Expressions like Humans Do. UCNLG+MT, pp. 84–86 (2007)
Gardent, C.: Generating minimal definite descriptions. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (2002)
Krahmer, E., Theune, M.: Efficient Context-Sensitive Generation of Referring Expressions. In: van Deemter, K., Kibble, R. (eds.) Information Sharing Reference and Presupposition in Language Generation and Interpretation, pp. 223–264. CSLI Publications, Stanford (2002)
Horacek, H.: Generating referential descriptions under conditions of uncertainty. In: 10th European workshop on Natural Language Generation, Aberdeen, pp. 58–67 (2005)
Siddharthan, A., Copestake, A.: Generating referring expressions in open domains. In: Proceeding of ACL 2004 (2004)
Beltz, A., Gatt, A.: The Attribute Selection for GRE Challenge: Overview and Evaluation Results. UCNLG+MT, pp. 75–83 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Lucena, D.J., Paraboni, I. (2008). Combining Frequent and Discriminating Attributes in the Generation of Definite Descriptions. In: Geffner, H., Prada, R., Machado Alexandre, I., David, N. (eds) Advances in Artificial Intelligence – IBERAMIA 2008. IBERAMIA 2008. Lecture Notes in Computer Science(), vol 5290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88309-8_26
Download citation
DOI: https://doi.org/10.1007/978-3-540-88309-8_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88308-1
Online ISBN: 978-3-540-88309-8
eBook Packages: Computer ScienceComputer Science (R0)