Graph-based generation of referring expressions
Computational Linguistics
Generating minimal definite descriptions
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning attribute selections for non-pronominal expressions
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Generating approximate geographic descriptions
Empirical methods in natural language generation
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Existing algorithms for the Generation of Referring Expressions (GRE) aim at generating descriptions that allow a hearer to identify its intended referent uniquely; the length of the expression is also considered, usually as a secondary issue. We explore the possibility of making the trade-off between these two factors more explicit, via a general cost function which scores these two aspects separately. We sketch some more complex phenomena which might be amenable to this treatment.