Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential

Figurative language, encompassing metaphor, hyperbole, and metonymy, is deeply embedded in Arabic discourse and presents considerable challenges related to Arabic’s rich morphology, dialectal diversity, and complex syntax. In response to these challenges, this study introduces a novel multi-layered ontology construction framework aimed at systematically capturing and formalizing linguistic features essential for the annotation of figurative language in Arabic texts. The proposed framework comprises four interrelated layers–Lexical, Grammatical, Inflectional, and Categorical–and integrates external lexical resources, such as Wiktionary, dependency parsing, and morphological analysis to model syntactic, morphological, and semantic relationships. The ontology supports key NLP applications, including word sense disambiguation, semantic search, and text summarization. Experimental evaluation demonstrates the scalability and effectiveness of the framework, resulting in the structured representation of over 41,000 Arabic lexical entries and approximately 830,000 morphological inflections. Theoretically, this work advances the formal modeling of figurative language in morphologically rich languages, while practically, it enables the development of more linguistically grounded and semantically aware Arabic NLP systems.

Abstract licence: CC BY-NC-ND

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