Based on the research direction of digitizing construction engineering standards, this study extends existing SNL-based single-sentence digitization technologies to address challenges in large-scale applications involving entire and multiple standards. Studies have found that in the process of large-scale application of standard digitization based on SNL, there are problems such as difficulty in storing and expressing implicit information within standards, lack of automatic classification and filtering methods for large quantities of provisions, and lack of effective inspection methods for similar provisions within the same standard or between different standards. This paper proposes a multi-dimensional label system with automated generation for SNL-based digitization scenarios and a rule similarity verification method for multiple SNL provisions. The solutions enhance digital expression capability, enable multi-dimensional clauses management, and improve accuracy and consistency of standardization outcomes, providing critical technical support for practical large-scale standard digitization applications.