Research on the Pathways and Challenges of Constructing Legal Corpus

Legal corpus serves as the core data foundation for Legal AI, playing an increasingly important role in fields such as natural language processing, legal reasoning systems, intelligent legal question-answering platforms, and legal policy analysis. However, constructing high-quality, secure, and compliant legal corpus still faces numerous practical pathways and challenges. This paper systematically explores the multidimensional pathways for constructing legal corpus, including data source selection, the collaboration between manual and machine annotation, the standardized management of legal terminology, the intelligent processing framework for legal corpus, and the data integration mechanism for multiple institution collaboration. At the same time, this paper analyzes the main challenges faced during the construction of legal corpus, such as data quality and standardization, the identification and handling of legally sensitive content, and the ongoing adaptability to legal policies. The research suggests that a combined approach of technological empowerment and institutional guarantees can effectively enhance data quality, ensure compliance and security, and achieve intelligent management in the construction of legal corpus. Finally, the paper proposes future research directions and practical recommendations, aiming to provide theoretical guidance and practical support for the construction and application of legal corpus.