Mathematics (Feb 2023)

Fuzzy Property Grammars for Gradience in Natural Language

  • Adrià Torrens-Urrutia,
  • Vilém Novák,
  • María Dolores Jiménez-López

DOI
https://doi.org/10.3390/math11030735
Journal volume & issue
Vol. 11, no. 3
p. 735

Abstract

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This paper introduces a new grammatical framework, Fuzzy Property Grammars (FPGr). This is a model based on Property Grammars and Fuzzy Natural Logic. Such grammatical framework is constraint-based and provides a new way to formally characterize gradience by representing grammaticality degrees regarding linguistic competence (without involving speakers judgments). The paper provides a formal-logical characterization of FPGr. A test of the framework is presented by implementing an FPGr for Spanish. FPGr is a formal theory that may serve linguists, computing scientists, and mathematicians since it can capture infinite grammatical structures within the variability of a language.

Keywords