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        <title>Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation</title>
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        <namePart type="given">Eduardo</namePart>
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    <name type="personal">
        <namePart type="given">Kees</namePart>
        <namePart type="family">Van Deemter</namePart>
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            <namePart type="given">Alexis</namePart>
            <namePart type="family">Palmer</namePart>
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            <namePart type="given">Jose</namePart>
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    <abstract>Some applications of artificial intelligence make it desirable that logical formulae be converted computationally to comprehensible natural language sentences. As there are many logical equivalents to a given formula, finding the most suitable equivalent to be used as input for such a “logic-to-text” generation system is a difficult challenge. In this paper, we focus on the role of brevity: Are the shortest formulae the most suitable? We focus on propositional logic (PL), framing formula minimization (i.e., the problem of finding the shortest equivalent of a given formula) as a Quantified Boolean Formulae (QBFs) satisfiability problem. We experiment with several generators and selection strategies to prune the resulting candidates. We conduct exhaustive automatic and human evaluations of the comprehensibility and fluency of the generated texts. The results suggest that while, in many cases, minimization has a positive impact on the quality of the sentences generated, formula minimization may ultimately not be the best strategy.</abstract>
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%0 Conference Proceedings
%T Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation
%A Calò, Eduardo
%A Levy, Jordi
%A Gatt, Albert
%A Van Deemter, Kees
%Y Palmer, Alexis
%Y Camacho-collados, Jose
%S Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F calo-etal-2023-shortest
%X Some applications of artificial intelligence make it desirable that logical formulae be converted computationally to comprehensible natural language sentences. As there are many logical equivalents to a given formula, finding the most suitable equivalent to be used as input for such a “logic-to-text” generation system is a difficult challenge. In this paper, we focus on the role of brevity: Are the shortest formulae the most suitable? We focus on propositional logic (PL), framing formula minimization (i.e., the problem of finding the shortest equivalent of a given formula) as a Quantified Boolean Formulae (QBFs) satisfiability problem. We experiment with several generators and selection strategies to prune the resulting candidates. We conduct exhaustive automatic and human evaluations of the comprehensibility and fluency of the generated texts. The results suggest that while, in many cases, minimization has a positive impact on the quality of the sentences generated, formula minimization may ultimately not be the best strategy.
%R 10.18653/v1/2023.starsem-1.17
%U https://aclanthology.org/2023.starsem-1.17
%U https://doi.org/10.18653/v1/2023.starsem-1.17
%P 180-192

Markdown (Informal)

[Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation](https://aclanthology.org/2023.starsem-1.17) (Calò et al., *SEM 2023)

• Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation (Calò et al., *SEM 2023)

ACL

• Eduardo Calò, Jordi Levy, Albert Gatt, and Kees Van Deemter. 2023. Is Shortest Always Best? The Role of Brevity in Logic-to-Text Generation. In Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), pages 180–192, Toronto, Canada. Association for Computational Linguistics.