Objective: With advancements in computer science and software engineering technologies, including artificial intelligence, domain-specific languages, and knowledge graphs, automated compliance checking tools are emerging. In the construction field, for example, research and practical applications in automated compliance checking for building information modeling (BIM) and architectural 2D drawings are thriving. A core step in conducting automated compliance checking with computers is the logical representation of articles written in natural language, transforming them into a format that computers can process. While extensive research has been conducted in this field and many widely used standards and paradigms have been developed, the handling of high-level inter-rule relationships remains largely unexplored. This study aims to propose a computer-representable method for high-level inter-rule relationships, enabling automated compliance checking systems to process such relationships automatically. Methods: To achieve the computer-representable formalization of these relationships, based on the summary and organization of actual building codes, this study introduces a paradigm within the context of rule-based automated compliance checking in the construction field. The paradigm includes three patterns: "compliance cascade", "non-compliance cascade", and "non-applicability cascade". The compliance cascade pattern represents "if rule A is compliant, then rule B will not be checked". Similarly, the non-compliance cascade pattern represents "if rule A is non-compliant, then rule B will not be checked", and the non-applicability cascade pattern indicates that "if rule A is not applicable, then rule B will not be checked". In each cascade pattern, corresponding indicators are used to designate the target rules. Among the rules in rule-based automated compliance checking systems, those expressed in the form of "if...then..." indicate that "rule A is not applicable" when the semantic model does not satisfy the "if" condition of rule A. This study also designs a corresponding execution engine for the paradigm using BIMChecker and structured natural language (SNL), enabling computers to process high-level inter-rule relationships automatically. The engine design adheres to the open-closed principle and single responsibility principle—two fundamental design principles—to ensure optimal extensibility. Results: To verify the paradigm's effectiveness and applicability, an experiment on representing high-level inter-rule relationships in actual codes using the proposed approach has been conducted. In addition, application experiments were carried out on 15 representative real-world projects via the Tsinghua "Tuzhi" platform. The results indicate that the paradigm exhibits strong validity and applicability across all 15 projects. Furthermore, the "Tuzhi" system is used to showcase the execution effects of high-level inter-rule relationships through a practical case study. Conclusions: This study proposes a representation method for high-level inter-rule relationships within rule-based automated compliance checking systems. Using three distinct patterns—"compliance cascade", "non-compliance cascade", and "non-applicability cascade"—it establishes a computer- interpretable framework for representing these relationships. By integrating an appropriate execution engine, this approach enhances rule-based automated compliance checking systems to generate check reports that closely align with human expert reasoning. Furthermore, the experiments in this study validate the effectiveness of the proposed patterns.