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

Abstract

Abstract Arabic is a linguistically and culturally rich language with a vast vocabulary that spans scientific, religious, and literary domains. However, 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 pipeline is designed to improve accuracy and minimize extraction noise. Its output undergoes validation through systematic quality checks and human review. Each record pairs a target word with its standardized Arabic definition and includes metadata specifying the source domain. The dataset encompasses terms from linguistics, Islamic studies, mathematics, physics, psychology, and engineering, supporting both computational linguistics and lexicographic research. Potential applications include reverse dictionary modeling, semantic retrieval, and educational tools. The release of this resource is intended to advance Arabic natural language processing and facilitate reproducible research on Arabic lexical semantics.