Suleiman Mohammad
Electronic Marketing and Social Media, Faculty of Economic and Administrative Sciences, Zarqa University, Zarqa 13115, Jordan
Faculty of Business and Communications, INTI International University, Negeri Sembilan 71800, Malaysia
Yogeesh N
Department of Mathematics, Government First Grade College, Tumkur, Karnataka 572102, India
Khaleel Ibrahim Al-Daoud
Department of Accounting, Business School Faculties, Al Ahilya Amman University, Amman 19111, Jordan
N Raja, Manoj C R
Department of English, Government First Grade College Kunigal, Karnataka 560001, India
Raghavendra M H
Department of English, Government First Grade College Kunigal, Karnataka 560001, India
Asokan Vasudevan
Faculty of Business and Communications, INTI International University, Negeri Sembilan 71800, Malaysia
Nawaf Alshdaifat
Faculty of Information Technology, Applied Science Private University, Amman 11937, Jordan
Mohammad Faleh Ahmmad Hunitie
Department of Public Administration, School of Business, University of Jordan, Amman 11942, Jordan
This study proposes a novel fuzzy grammar model to analyze the syntax-pragmatics interface by integrating fuzzy logic into linguistic evaluation. Traditional binary models of grammaticality fail to capture the graded acceptability observed in natural language, where subtle variations in syntactic structure and contextual cues interact to determine overall language performance. Our approach normalizes Likert-scale ratings of syntactic well-formedness and pragmatic appropriateness into fuzzy membership values, enabling a continuous representation of linguistic acceptability. The model employs fuzzy membership functions—primarily using linear normalization—and aggregates syntactic and pragmatic scores using the minimum operator to reflect the principle that a sentence is as acceptable as its weakest component. A small experimental dataset comprising five sentences was used to illustrate the model’s implementation, where descriptive statistics, visual bar charts, and fuzzy inference outputs demonstrated that sentences with inconsistent syntactic and pragmatic ratings yield lower overall acceptability. The results underscore fuzzy logic’s efficacy in distinguishing borderline cases and capturing the nuanced interplay between formal structure and context-sensitive meaning. This integrative framework not only extends theoretical insight into language processing but also offers promising applications in natural language processing, language education, and cross-linguistic studies. Future research should empirically validate the model with larger datasets and explore alternative fuzzy aggregation strategies.
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Copyright © 2025 Suleiman Mohammad, Yogeesh N, Khaleel Ibrahim Al-Daoud, N Raja, Manoj C R, Raghavendra M H, Asokan Vasudevan, Nawaf Alshdaifat, Mohammad Faleh Ahmmad Hunitie
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
