ASRD: Development and Validation of a Large-Scale Arabic Semantic Relation Dataset

ASRD: Development and Validation of a Large-Scale Arabic Semantic Relation Dataset | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ASRD: Development and Validation of a Large-Scale Arabic Semantic Relation Dataset Randah Alharbi, Tarek Helmy, Atika Al-Saghyir, Safa Aglan, Abdulrahman Alosaimy, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7602223/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper presents the development and validation of the Arabic Semantic Relations Dataset (ASRD), a large-scale and high-quality lexical resource designed to support research in Arabic lexical semantics. ASRD addresses the lack of robust, publicly available Arabic datasets annotated for semantic relations, especially hypernymy. It was built by aggregating and aligning data from multiple Arabic lexical sources, followed by extensive cleaning, annotation, and validation processes. Validation was conducted in collaboration with expert Arabic linguists. We describe the sources, extraction pipeline, structural characteristics, and validation strategy, and demonstrate the dataset’s utility in downstream NLP tasks such as hypernymy detection and hypernymy directionality. The dataset is publicly available at Zenodo https://doi.org/10.5281/zenodo.15486725. Hypernymy Annotation and Validation Semantic Relations Dataset Construction Arabic Lexical Semantics Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7602223","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":557781733,"identity":"518d3a78-c6ff-40b5-b256-50cdc29f0dc6","order_by":0,"name":"Randah 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