Arabic Legal NLP and Legal Hallucinations

Legal hallucination in Arabic large language models (LLMs) represents a growing challenge for the integrity of AIassisted legal work. This study examines the structural relationship between the deficiencies of Arabic Legal Natural Language Processing (NLP) systems and the emergence of legal hallucinations, with a particular focus on the Egyptian legal context. The research adopts a qualitative doctrinal methodology combined with an empirical evaluation. It draws on existing literature in Arabic NLP, AI hallucination, and legal theory, while conducting direct testing of two leading LLMs-ChatGPT and Gemini-using Egyptian statutory and judicial materials to observe and classify hallucination patterns in practice. The study finds that legal hallucinations in Arabic LLMs are not random errors; they follow identifiable patterns rooted in three core deficiencies: the scarcity and imbalance of Arabic legal datasets, the linguistic complexity of Arabic legal language (including semantic ambiguity, polysemy, and the presence of Islamic jurisprudence terminology), and the fundamental absence of genuine legal reasoning in current AI architectures. Based on empirical testing, the study proposes a six-category taxonomy of Arabic legal hallucinations, including citation hallucination, contextual hallucination, temporal hallucination, fabricated judicial citation, doctrinal hallucination, and hierarchical reasoning failure. To mitigate these risks, the study proposes a four-layer framework comprising: building robust Arabic legal data infrastructure, implementing Retrieval-Augmented Generation (RAG) for hallucination control, maintaining meaningful human oversight through lawyer and judicial review, and establishing regulatory governance frameworks aligned with international AI standards. The findings contribute to the emerging field of Arabic Legal AI by providing a structured classification of hallucination types and a practical mitigation framework, with direct implications for legal practitioners, AI developers, and policymakers working within Arab legal systems.