MURAD: A Large-Scale Multi-Domain Unified Reverse Arabic Dictionary Dataset

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Authors: Serry Sibaee, Yasser Alhabashi, Nadia Samer Sibai, Yara A. Farouk, Adel Ammar, Sawsan AlHalawani, Wadii Boulila
Cited by: 0

Abstract

Arabic is a linguistically and culturally rich language with a vast vocabulary that spans scientific, religious, and literary domains. Yet, large-scale lexical datasets linking Arabic words to precise definitions remain limited. We present MURAD (Multi-domain Unified Reverse Arabic Dictionary), an open lexical dataset with 96,243 word-definition pairs. The data come from trusted reference works and educational sources. Extraction used a hybrid pipeline integrating direct text parsing, optical character recognition, and automated reconstruction. This ensures accuracy and clarity. Each record aligns a target word with its standardized Arabic definition and metadata that identifies the source domain. The dataset covers terms from linguistics, Islamic studies, mathematics, physics, psychology, and engineering. It supports computational linguistics and lexicographic research. Applications include reverse dictionary modeling, semantic retrieval, and educational tools. By releasing this resource, we aim to advance Arabic natural language processing and promote reproducible research on Arabic lexical semantics.

Fields of Study & Subjects

Natural Language Processing Techniques Lexicography and Language Studies Topic Modeling

Publication details

Journal / source
arXiv (Cornell University)
Publication date
29 January 2026
Document type
Preprint