Fuzzy Property Grammars for Gradience in Natural Language

Identificador:  imarina:9291935

Handle: https://hdl.handle.net/20.500.11797/imarina9291935

Autores:  Torrens-Urrutia, Adria; Novak, Vilem; Jimenez-Lopez, Maria Dolores

Resumen:
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.