The fuzzy logic approach is applicable to model the domain knowledge when it includes heuristic rules with vague, ill-defined, or approximate conditions. To enable the knowledge representation for electronic processing, a number of researchers have suggested diverse types of markup languages to formalize building regulatory rules and guidelines. The common method utilizing natural language processing algorithms begins with generating ontology to capture domain knowledge to improve the interpretability and understanding of domain-specific content. The elasticity of the text is crucial for a system of knowledge acquisition, yet engineers and architects can consume those documents and translate them into formal scientific representations and software applications. The artificial intelligence methods of modeling human languages utilize various natural language processing (NLP) algorithms to drive meaning from the provided natural language text. Numerous challenges in NLP methods include natural language understanding and extracting rules from building regulation documents.