The Semantic Annotation of the Quran Corpus Based on Hierarchical Network of Concepts Theory

This Quran as the central religious text of Islam is widely regarded as the finest work in classical Arabic literature and plays an important role in Islam world. This paper studied and analyzed the Quran Chinese and English data, built the Quran Chinese and English words semantic knowledge base in which the grammar and semantic information of the Quranic words were described based on HNC theory, built the Quran semantic annotation corpus in which the part of speech and semantic description were annotated. The corpus with semantic annotation can help us identify the same meaning with different word forms. This paper proposed a new method of semantic analysis to solve the semantic similarity problem of natural language processing, which will benefit both the research on the semantic analysis in Natural Language Processing and the development of the Islamic Cultures.