Keywords
Abstract
Controlled Natural Language (CNL) applied to construction regulatory and technical documents is examined as a linguistic mechanism for eliminating ambiguity and enabling automated interpretation of requirements. The research object is the language of normative and technical documents used in construction, which is traditionally characterized by syntactic complexity, terminological inconsistency, and stylistic variability that hinder digital processing and automated compliance checking. The research method is based on a systematic review and content analysis of peer-reviewed scientific publications indexed in Scopus and Web of Science, focusing on controlled languages, template-based requirement formulation, ontology-driven approaches, and natural language processing techniques integrated with Building Information Modeling. The research results demonstrate that the use of controlled language significantly increases the accuracy of requirement extraction, enables direct transformation of textual provisions into formal, machine-executable rules, and reduces interpretative variability. Empirical evidence from existing controlled-language implementations confirms improvements in automated compliance checking performance, enhanced terminology consistency, and greater interoperability between regulatory texts and digital construction models. The findings indicate that controlled language constitutes a foundational component for the development of machine-readable regulatory frameworks, supporting the transition toward digital regulations and automated compliance processes in the construction industry.