Describing Linguistic Vagueness of Evaluative Expressions Using Fuzzy Natural Logic and Linguistic Constraints

Adrià Torrens-Urrutia, Vilém Novák and María Dolores Jiménez-López
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Adrià Torrens-Urrutia: Research Group on Mathematical Linguistics (GRLMC), Universitat Rovira i Virgili, 43002 Tarragona, Spain
Vilém Novák: Institute for Research and Applications of Fuzzy Modeling (IRAFM), University of Ostrava, 701 03 Ostrava, Czech Republic
María Dolores Jiménez-López: Research Group on Mathematical Linguistics (GRLMC), Universitat Rovira i Virgili, 43002 Tarragona, Spain

Mathematics, 2022, vol. 10, issue 15, 1-24

Abstract: In recent years, the study of evaluative linguistic expressions has crossed the field of theoretical linguistics and has aroused interest in very different research areas such as artificial intelligence, psychology or cognitive linguistics. The interest in this type of expressions may be due to its relevance in applications such as opinion mining or sentiment analysis. This paper brings together Fuzzy Natural Logic and Fuzzy Property Grammars to approach evaluative expressions. Our contribution includes the marriage of mathematical and linguistic methods for providing a formalism to deal with the linguistic vagueness of evaluative expressions by describing the syntax and semantics of these structures. We contribute to the study of evaluative linguistic expressions by proposing a formal characterization of them where the concepts of semantic prime, borderline evaluative expressions and markedness are defined and where the relation between the semantic constraints of evaluations and their sentiment can be established. A proof-of-concept of how to create a lexicon of evaluative expressions for future computational applications is presented. The results demonstrate that linguistic evaluative expressions are gradient, have sentiment, and that the evaluations work as a relation of hypernym and hyponym, the hypernym being a semantic prime. Our findings provide the basis for building an ontology of evaluative expressions for future computational applications.

Keywords: evaluative expressions; linguistic gradience; fuzzy grammar; linguistic constraints; grammaticality; sentiment analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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