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

TL;DR

MURAD is a comprehensive, multi-domain Arabic lexical dataset with over 96,000 word-definition pairs, designed to support NLP and lexicographic research through accurate, domain-annotated data.

Contribution

This paper introduces MURAD, the first large-scale, multi-domain reverse Arabic dictionary dataset with verified entries from diverse sources, enhancing Arabic NLP resources.

Findings

Dataset contains 96,243 word-definition pairs.

Includes terms from multiple scientific and literary domains.

Supports applications like reverse dictionary modeling and semantic retrieval.

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.