@inproceedings{araujo-etal-2010-sinotas,
title = "{SIN}otas: the Evaluation of a {NLG} Application",
author = "Araujo, Roberto P. A. and
de Oliveira, Rafael L. and
de Novais, Eder M. and
Tadeu, Thiago D. and
Pereira, Daniel B. and
Paraboni, Ivandr{\'e}",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf",
abstract = "SINotas is a data-to-text NLG application intended to produce short textual reports on students academic performance from a database conveying their grades, weekly attendance rates and related academic information. Although developed primarily as a testbed for Portuguese Natural Language Generation, SINotas generates reports of interest to both students keen to learn how their professors would describe their efforts, and to the professors themselves, who may benefit from an at-a-glance view of the students performance. In a traditional machine learning approach, SINotas uses a data-text aligned corpus as training data for decision-tree induction. The current system comprises a series of classifiers that implement major Document Planning subtasks (namely, data interpretation, content selection, within- and between-sentence structuring), and a small surface realisation grammar of Brazilian Portuguese. In this paper we focus on the evaluation work of the system, applying a number of intrinsic and user-based evaluation metrics to a collection of text reports generated from real application data.",
}
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%0 Conference Proceedings
%T SINotas: the Evaluation of a NLG Application
%A Araujo, Roberto P. A.
%A de Oliveira, Rafael L.
%A de Novais, Eder M.
%A Tadeu, Thiago D.
%A Pereira, Daniel B.
%A Paraboni, Ivandré
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F araujo-etal-2010-sinotas
%X SINotas is a data-to-text NLG application intended to produce short textual reports on students academic performance from a database conveying their grades, weekly attendance rates and related academic information. Although developed primarily as a testbed for Portuguese Natural Language Generation, SINotas generates reports of interest to both students keen to learn how their professors would describe their efforts, and to the professors themselves, who may benefit from an at-a-glance view of the students performance. In a traditional machine learning approach, SINotas uses a data-text aligned corpus as training data for decision-tree induction. The current system comprises a series of classifiers that implement major Document Planning subtasks (namely, data interpretation, content selection, within- and between-sentence structuring), and a small surface realisation grammar of Brazilian Portuguese. In this paper we focus on the evaluation work of the system, applying a number of intrinsic and user-based evaluation metrics to a collection of text reports generated from real application data.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf
Markdown (Informal)
[SINotas: the Evaluation of a NLG Application](http://www.lrec-conf.org/proceedings/lrec2010/pdf/593_Paper.pdf) (Araujo et al., LREC 2010)
ACL
- Roberto P. A. Araujo, Rafael L. de Oliveira, Eder M. de Novais, Thiago D. Tadeu, Daniel B. Pereira, and Ivandré Paraboni. 2010. SINotas: the Evaluation of a NLG Application. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).