构建了9.6万条阿拉伯语反向词典数据集，助力语言技术研究。
MURAD: A Large-Scale Multi-Domain Unified Reverse Arabic Dictionary Dataset
- 融合文本解析与OCR的混合流程提取词义对。
- 覆盖9大领域共96,243个标准化词义配对。
- 适合做阿拉伯语语义分析、教育工具开发的研究者使用。
阿拉伯语是语言与文化兼具的丰富语言，词汇涵盖科学、宗教和文学等多个领域，但大规模精准词义对应的数据集仍较匮乏。本文提出MURAD（多领域统一阿拉伯语反向词典），一个包含96,243个词义对的开放词汇数据集。数据源自可信参考文献与教育资料，通过结合直接文本解析、光学字符识别与自动化重建的混合流程提取，确保准确性与清晰性。每条记录将目标词与其标准阿拉伯语定义关联，并标注来源领域信息。数据覆盖语言学、伊斯兰研究、数学、物理、心理学及工程等领域。该数据集支持计算语言学与词典学研究，可应用于反向词典建模、语义检索与教育工具开发。开源发布旨在推动阿拉伯语自然语言处理发展，并促进阿拉伯语词汇语义研究的可复现性。
原文摘要 · Abstract (English)
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.
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