Category-Driven Content Selection

Rania Mohammed, Laura Perez-Beltrachini, Claire Gardent

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper, we introduce a content selection method where the communicative goal is to describe entities of different categories (e.g., astronauts, universities or monuments). We argue that this method provides an interesting basis both for generating descriptions of entities and for semi-automatically constructing a
benchmark on which to train, test and compare data-to-text generation systems.
Original languageEnglish
Title of host publicationProceedings of The 9th International Natural Language Generation conference
PublisherAssociation for Computational Linguistics
Number of pages5
Publication statusPublished - 8 Sep 2016
Event9th International Natural Language Generation conference - Edinburgh, United Kingdom
Duration: 5 Sep 20168 Sep 2016


Conference9th International Natural Language Generation conference
Abbreviated titleINLG 2016
Country/TerritoryUnited Kingdom
Internet address

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