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

2026-01-29

AI Summary

Arabic lacks large-scale, multi-domain aligned word-definition datasets, hindering progress in natural language processing and lexicography. To address this gap, this work presents MURAD, the first open-vocabulary dataset for Arabic comprising 96,243 word-definition pairs, curated from authoritative dictionaries spanning linguistics, Islamic studies, mathematics, physics, psychology, and engineering. A hybrid data extraction pipeline—integrating direct text parsing, optical character recognition (OCR), and automated reconstruction techniques—ensures high accuracy, consistent formatting, and rich source-domain metadata. MURAD supports diverse downstream tasks such as reverse dictionary modeling and semantic retrieval, offering a high-quality foundational resource for Arabic computational linguistics, educational tool development, and reproducible research.

Technology Category

• Natural Language Processing: Lexical Semantics and Morphology
• Data Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

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.

Problem

• Arabic lexical resources
• reverse dictionary
• multi-domain dataset
• lexical semantics
• natural language processing

Innovation

• Arabic lexical semantics
• reverse dictionary
• multi-domain dataset
• hybrid data extraction
• optical character recognition