Using logic in the generation of referring expressions

The problem of generating referring expressions (GRE) is an important task in natural language generation. In this paper, we advocate for the use of logical languages in the output of the content determination phase (i.e., when the relevant features of the object to be referred are selected). Many d...

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Detalles Bibliográficos
Autores principales:	Areces, Carlos Eduardo, Figueira, Santiago Daniel, Gorín, Daniel Alejandro
Publicado:	2011
Materias:	Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Realizability Referring expressions Relevant features Computational linguistics Logic programming Natural language processing systems Linguistics Computational complexity Computer circuits
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v6736LNAI_n_p17_Areces http://hdl.handle.net/20.500.12110/paper_03029743_v6736LNAI_n_p17_Areces
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	paper:paper_03029743_v6736LNAI_n_p17_Areces
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spelling	paper:paper_03029743_v6736LNAI_n_p17_Areces2023-06-08T15:28:40Z Using logic in the generation of referring expressions Areces, Carlos Eduardo Figueira, Santiago Daniel Gorín, Daniel Alejandro Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Realizability Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Referring expressions Relevant features Computational linguistics Logic programming Natural language processing systems Computational linguistics Linguistics Logic programming Natural language processing systems Computational complexity Computer circuits The problem of generating referring expressions (GRE) is an important task in natural language generation. In this paper, we advocate for the use of logical languages in the output of the content determination phase (i.e., when the relevant features of the object to be referred are selected). Many different logics can be used for this and we argue that, for a particular application, the actual choice shall constitute a compromise between expressive power (how many objects can be distinguished), computational complexity (how difficult it is to determine the content) and realizability (how often will the selected content be realized to an idiomatic expression). We show that well-known results from the area of computational logic can then be transferred to GRE. Moreover, our approach is orthogonal to previous proposals and we illustrate this by generalizing well-known content-determination algorithms to make them parametric on the logic employed. © 2011 Springer-Verlag Berlin Heidelberg. Fil:Areces, C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Figueira, S. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Gorín, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2011 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v6736LNAI_n_p17_Areces http://hdl.handle.net/20.500.12110/paper_03029743_v6736LNAI_n_p17_Areces
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Realizability Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Referring expressions Relevant features Computational linguistics Logic programming Natural language processing systems Computational linguistics Linguistics Logic programming Natural language processing systems Computational complexity Computer circuits
spellingShingle	Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Realizability Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Referring expressions Relevant features Computational linguistics Logic programming Natural language processing systems Computational linguistics Linguistics Logic programming Natural language processing systems Computational complexity Computer circuits Areces, Carlos Eduardo Figueira, Santiago Daniel Gorín, Daniel Alejandro Using logic in the generation of referring expressions
topic_facet	Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Realizability Computational logic Content determination Expressive power Generating referring expressions Logical language Natural language generation Referring expressions Relevant features Computational linguistics Logic programming Natural language processing systems Computational linguistics Linguistics Logic programming Natural language processing systems Computational complexity Computer circuits
description	The problem of generating referring expressions (GRE) is an important task in natural language generation. In this paper, we advocate for the use of logical languages in the output of the content determination phase (i.e., when the relevant features of the object to be referred are selected). Many different logics can be used for this and we argue that, for a particular application, the actual choice shall constitute a compromise between expressive power (how many objects can be distinguished), computational complexity (how difficult it is to determine the content) and realizability (how often will the selected content be realized to an idiomatic expression). We show that well-known results from the area of computational logic can then be transferred to GRE. Moreover, our approach is orthogonal to previous proposals and we illustrate this by generalizing well-known content-determination algorithms to make them parametric on the logic employed. © 2011 Springer-Verlag Berlin Heidelberg.
author	Areces, Carlos Eduardo Figueira, Santiago Daniel Gorín, Daniel Alejandro
author_facet	Areces, Carlos Eduardo Figueira, Santiago Daniel Gorín, Daniel Alejandro
author_sort	Areces, Carlos Eduardo
title	Using logic in the generation of referring expressions
title_short	Using logic in the generation of referring expressions
title_full	Using logic in the generation of referring expressions
title_fullStr	Using logic in the generation of referring expressions
title_full_unstemmed	Using logic in the generation of referring expressions
title_sort	using logic in the generation of referring expressions
publishDate	2011
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v6736LNAI_n_p17_Areces http://hdl.handle.net/20.500.12110/paper_03029743_v6736LNAI_n_p17_Areces
work_keys_str_mv	AT arecescarloseduardo usinglogicinthegenerationofreferringexpressions AT figueirasantiagodaniel usinglogicinthegenerationofreferringexpressions AT gorindanielalejandro usinglogicinthegenerationofreferringexpressions
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Using logic in the generation of referring expressions

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