Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

1.2 COMPUTER AND INFORMATION SCIENCE

Publication Details

In Proceedings of the MT Summit XI Workshop Using Corpora for Natural Language Generation: Language Generation and Machine Translation (UCNLG+MT), Pages 90-92. Blez, A. and Varges, S. (eds).

Abstract

The DIT system uses an incremental greedy search to generate descriptions, similar to the incremental algorithm described in (Dale and Reiter, 1995). The selection of the next attribute to be tested for inclusion in the description is ordered by the absolute frequency of each attribute in the training corpus. Attributes are selected in descending order of frequency (i.e. the attribute that occurred most frequently in the training corpus is selected first). Where two or more attributes have the same frequency of occurrence the first attribute found with that frequency is selected. The type attribute is always included in the description. Other attributes are included in the description if they exclude at least 1 distractor from the set of distractors that fulfil the description generated prior that attribute’s selection.The algorithm terminates when a distinguishing description has been generated (i.e., all the distractors have been excluded) or when all the target’s attributes have been tested for inclusion in the description.

DOI

https://doi.org/10.21427/y7gh-m319

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