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 mul...

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Main Authors: Zouheir Banou, Sanaa El Filali, El Habib Benlahmar, Laila Eljiani, Fatima-Zahra Alaoui
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
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Online Access:https://ieeexplore.ieee.org/document/11112775/
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author Zouheir Banou
Sanaa El Filali
El Habib Benlahmar
Laila Eljiani
Fatima-Zahra Alaoui
author_facet Zouheir Banou
Sanaa El Filali
El Habib Benlahmar
Laila Eljiani
Fatima-Zahra Alaoui
author_sort Zouheir Banou
collection DOAJ
description 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.
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spelling doaj-art-38cdcb913b3448eea93bb99d64be03842025-08-20T04:01:48ZengIEEEIEEE Access2169-35362025-01-011313853513855010.1109/ACCESS.2025.359613011112775Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language PotentialZouheir Banou0https://orcid.org/0000-0002-6427-2342Sanaa El Filali1https://orcid.org/0000-0002-4076-9581El Habib Benlahmar2Laila Eljiani3Fatima-Zahra Alaoui4Laboratory of Artificial Intelligence and Systems, Faculty of Sciences Ben M’Sick, Hassan II University of Casablanca, Casablanca, MoroccoLaboratory of Artificial Intelligence and Systems, Faculty of Sciences Ben M’Sick, Hassan II University of Casablanca, Casablanca, MoroccoLaboratory of Artificial Intelligence and Systems, Faculty of Sciences Ben M’Sick, Hassan II University of Casablanca, Casablanca, MoroccoLaboratory of Artificial Intelligence and Systems, Faculty of Sciences Ben M’Sick, Hassan II University of Casablanca, Casablanca, MoroccoLaboratory of Artificial Intelligence and Systems, Faculty of Sciences Ben M’Sick, Hassan II University of Casablanca, Casablanca, MoroccoFigurative 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.https://ieeexplore.ieee.org/document/11112775/Arabic ontologyfigurative language annotationlexical relationshipsnatural language processing (NLP)
spellingShingle Zouheir Banou
Sanaa El Filali
El Habib Benlahmar
Laila Eljiani
Fatima-Zahra Alaoui
Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential
IEEE Access
Arabic ontology
figurative language annotation
lexical relationships
natural language processing (NLP)
title Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential
title_full Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential
title_fullStr Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential
title_full_unstemmed Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential
title_short Developing a Multi-Layer Ontology Construction Framework for Arabic Language Processing: Focus on Figurative Language Potential
title_sort developing a multi layer ontology construction framework for arabic language processing focus on figurative language potential
topic Arabic ontology
figurative language annotation
lexical relationships
natural language processing (NLP)
url https://ieeexplore.ieee.org/document/11112775/
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