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            <namePart type="given">Leonor</namePart>
            <namePart type="family">Becerra-Bonache</namePart>
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            <namePart type="given">Dolores</namePart>
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            <namePart type="given">Carlos</namePart>
            <namePart type="family">Martín-Vide</namePart>
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    <abstract>This paper presents an approach to evaluate complexity of a given natural language input by means of a Fuzzy Grammar with some fuzzy logic formulations. Usually, the approaches in linguistics has described a natural language grammar by means of discrete terms. However, a grammar can be explained in terms of degrees by following the concepts of linguistic gradience &amp; fuzziness. Understanding a grammar as a fuzzy or gradient object allows us to establish degrees of grammaticality for every linguistic input. This shall be meaningful for linguistic complexity considering that the less grammatical an input is the more complex its processing will be. In this regard, the degree of complexity of a linguistic input (which is a linguistic representation of a natural language expression) depends on the chosen grammar. The bases of the fuzzy grammar are shown here. Some of these are described by Fuzzy Type Theory. The linguistic inputs are characterized by constraints through a Property Grammar.</abstract>
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%0 Conference Proceedings
%T An Approach to Measuring Complexity with a Fuzzy Grammar & Degrees of Grammaticality
%A Torrens Urrutia, Adrià
%Y Becerra-Bonache, Leonor
%Y Jiménez-López, M. Dolores
%Y Martín-Vide, Carlos
%Y Torrens-Urrutia, Adrià
%S Proceedings of the Workshop on Linguistic Complexity and Natural Language Processing
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New-Mexico
%F torrens-urrutia-2018-approach
%X This paper presents an approach to evaluate complexity of a given natural language input by means of a Fuzzy Grammar with some fuzzy logic formulations. Usually, the approaches in linguistics has described a natural language grammar by means of discrete terms. However, a grammar can be explained in terms of degrees by following the concepts of linguistic gradience & fuzziness. Understanding a grammar as a fuzzy or gradient object allows us to establish degrees of grammaticality for every linguistic input. This shall be meaningful for linguistic complexity considering that the less grammatical an input is the more complex its processing will be. In this regard, the degree of complexity of a linguistic input (which is a linguistic representation of a natural language expression) depends on the chosen grammar. The bases of the fuzzy grammar are shown here. Some of these are described by Fuzzy Type Theory. The linguistic inputs are characterized by constraints through a Property Grammar.
%U https://aclanthology.org/W18-4607
%P 59-67

Markdown (Informal)

[An Approach to Measuring Complexity with a Fuzzy Grammar & Degrees of Grammaticality](https://aclanthology.org/W18-4607) (Torrens Urrutia, 2018)

• An Approach to Measuring Complexity with a Fuzzy Grammar & Degrees of Grammaticality (Torrens Urrutia, 2018)

ACL

• Adrià Torrens Urrutia. 2018. An Approach to Measuring Complexity with a Fuzzy Grammar & Degrees of Grammaticality. In Proceedings of the Workshop on Linguistic Complexity and Natural Language Processing, pages 59–67, Santa Fe, New-Mexico. Association for Computational Linguistics.