@inproceedings{mille-etal-2019-teaching,
title = "Teaching {FORG}e to Verbalize {DB}pedia Properties in {S}panish",
author = "Mille, Simon and
Dasiopoulou, Stamatia and
Fisas, Beatriz and
Wanner, Leo",
editor = "van Deemter, Kees and
Lin, Chenghua and
Takamura, Hiroya",
booktitle = "Proceedings of the 12th International Conference on Natural Language Generation",
month = oct # "{--}" # nov,
year = "2019",
address = "Tokyo, Japan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-8659",
doi = "10.18653/v1/W19-8659",
pages = "473--483",
abstract = "Statistical generators increasingly dominate the research in NLG. However, grammar-based generators that are grounded in a solid linguistic framework remain very competitive, especially for generation from deep knowledge structures. Furthermore, if built modularly, they can be ported to other genres and languages with a limited amount of work, without the need of the annotation of a considerable amount of training data. One of these generators is FORGe, which is based on the Meaning-Text Model. In the recent WebNLG challenge (the first comprehensive task addressing the mapping of RDF triples to text) FORGe ranked first with respect to the overall quality in human evaluation. We extend the coverage of FORGE{'}s open source grammatical and lexical resources for English, so as to further improve the English texts, and port them to Spanish, to achieve a comparable quality. This confirms that, as already observed in the case of SimpleNLG, a robust universal grammar-driven framework and a systematic organization of the linguistic resources can be an adequate choice for NLG applications.",
}
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<abstract>Statistical generators increasingly dominate the research in NLG. However, grammar-based generators that are grounded in a solid linguistic framework remain very competitive, especially for generation from deep knowledge structures. Furthermore, if built modularly, they can be ported to other genres and languages with a limited amount of work, without the need of the annotation of a considerable amount of training data. One of these generators is FORGe, which is based on the Meaning-Text Model. In the recent WebNLG challenge (the first comprehensive task addressing the mapping of RDF triples to text) FORGe ranked first with respect to the overall quality in human evaluation. We extend the coverage of FORGE’s open source grammatical and lexical resources for English, so as to further improve the English texts, and port them to Spanish, to achieve a comparable quality. This confirms that, as already observed in the case of SimpleNLG, a robust universal grammar-driven framework and a systematic organization of the linguistic resources can be an adequate choice for NLG applications.</abstract>
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%0 Conference Proceedings
%T Teaching FORGe to Verbalize DBpedia Properties in Spanish
%A Mille, Simon
%A Dasiopoulou, Stamatia
%A Fisas, Beatriz
%A Wanner, Leo
%Y van Deemter, Kees
%Y Lin, Chenghua
%Y Takamura, Hiroya
%S Proceedings of the 12th International Conference on Natural Language Generation
%D 2019
%8 oct–nov
%I Association for Computational Linguistics
%C Tokyo, Japan
%F mille-etal-2019-teaching
%X Statistical generators increasingly dominate the research in NLG. However, grammar-based generators that are grounded in a solid linguistic framework remain very competitive, especially for generation from deep knowledge structures. Furthermore, if built modularly, they can be ported to other genres and languages with a limited amount of work, without the need of the annotation of a considerable amount of training data. One of these generators is FORGe, which is based on the Meaning-Text Model. In the recent WebNLG challenge (the first comprehensive task addressing the mapping of RDF triples to text) FORGe ranked first with respect to the overall quality in human evaluation. We extend the coverage of FORGE’s open source grammatical and lexical resources for English, so as to further improve the English texts, and port them to Spanish, to achieve a comparable quality. This confirms that, as already observed in the case of SimpleNLG, a robust universal grammar-driven framework and a systematic organization of the linguistic resources can be an adequate choice for NLG applications.
%R 10.18653/v1/W19-8659
%U https://aclanthology.org/W19-8659
%U https://doi.org/10.18653/v1/W19-8659
%P 473-483
Markdown (Informal)
[Teaching FORGe to Verbalize DBpedia Properties in Spanish](https://aclanthology.org/W19-8659) (Mille et al., INLG 2019)
ACL
- Simon Mille, Stamatia Dasiopoulou, Beatriz Fisas, and Leo Wanner. 2019. Teaching FORGe to Verbalize DBpedia Properties in Spanish. In Proceedings of the 12th International Conference on Natural Language Generation, pages 473–483, Tokyo, Japan. Association for Computational Linguistics.