@inproceedings{perez-beltrachini-etal-2016-building,
title = "Building {RDF} Content for Data-to-Text Generation",
author = "Perez-Beltrachini, Laura and
Sayed, Rania and
Gardent, Claire",
editor = "Matsumoto, Yuji and
Prasad, Rashmi",
booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/C16-1141",
pages = "1493--1502",
abstract = "In Natural Language Generation (NLG), one important limitation is the lack of common benchmarks on which to train, evaluate and compare data-to-text generators. In this paper, we make one step in that direction and introduce a method for automatically creating an arbitrary large repertoire of data units that could serve as input for generation. Using both automated metrics and a human evaluation, we show that the data units produced by our method are both diverse and coherent.",
}
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%0 Conference Proceedings
%T Building RDF Content for Data-to-Text Generation
%A Perez-Beltrachini, Laura
%A Sayed, Rania
%A Gardent, Claire
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F perez-beltrachini-etal-2016-building
%X In Natural Language Generation (NLG), one important limitation is the lack of common benchmarks on which to train, evaluate and compare data-to-text generators. In this paper, we make one step in that direction and introduce a method for automatically creating an arbitrary large repertoire of data units that could serve as input for generation. Using both automated metrics and a human evaluation, we show that the data units produced by our method are both diverse and coherent.
%U https://aclanthology.org/C16-1141
%P 1493-1502
Markdown (Informal)
[Building RDF Content for Data-to-Text Generation](https://aclanthology.org/C16-1141) (Perez-Beltrachini et al., COLING 2016)
ACL
- Laura Perez-Beltrachini, Rania Sayed, and Claire Gardent. 2016. Building RDF Content for Data-to-Text Generation. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1493–1502, Osaka, Japan. The COLING 2016 Organizing Committee.