SINotas: the evaluation of a NLG application (2010)
- Authors:
- Autor USP: PARABONI, IVANDRE - EACH
- Unidade: EACH
- Assunto: LINGUAGEM NATURAL
- Language: Inglês
- Imprenta:
- Publisher: European Language Resources Association (ELRA)
- Publisher place: Paris
- Date published: 2010
- ISBN: 2951740867
- Source:
- Título: Proceedings
- Conference titles: International Conference on Language Resources and Evaluation - LREC
-
ABNT
ARAUJO, Roberto Paulo Andrioli de et al. SINotas: the evaluation of a NLG application. 2010, Anais.. Paris: European Language Resources Association (ELRA), 2010. Disponível em: http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf. Acesso em: 20 jan. 2026. -
APA
Araujo, R. P. A. de, Oliveira, R. L. de, Novais, E. M. de, Tadeu, T. D., Pereira, D. B., & Paraboni, I. (2010). SINotas: the evaluation of a NLG application. In Proceedings. Paris: European Language Resources Association (ELRA). Recuperado de http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf -
NLM
Araujo RPA de, Oliveira RL de, Novais EM de, Tadeu TD, Pereira DB, Paraboni I. SINotas: the evaluation of a NLG application [Internet]. Proceedings. 2010 ;[citado 2026 jan. 20 ] Available from: http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf -
Vancouver
Araujo RPA de, Oliveira RL de, Novais EM de, Tadeu TD, Pereira DB, Paraboni I. SINotas: the evaluation of a NLG application [Internet]. Proceedings. 2010 ;[citado 2026 jan. 20 ] Available from: http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf - Zoom: a corpus of natural language descriptions of map locations
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- Gerando expressões de referência com a "quantidade certa" de informação
- Reference and the facilitation of search in spatial domains
- Lausanne: a framework for collaborative online NLP experiments
- Combining frequent and discriminating attributes in the generation of definite descriptions
- Personality-dependent content selection in natural language generation systems
- The design of an experiment in anaphora resolution for referring expressions generation
- Using ‘low-cost’ learning features for pronoun resolution
- Generating spatial referring expressions in interactive 3D worlds
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