PARSING CONSTRUCTION STANDARDS INTO MACHINE-PROCESSABLE FORMAT

Abstract: Current BIM-based compliance checking still relies heavily on manually interpreting construction standards, as regulatory texts are complex and unstructured. This limits scalability, consistency, and automation. This paper presents an NLP-based pipeline using a fine-tuned T5 transformer model to automatically extract structured Information Requirements from German construction standards (DIN 4108-2, -3, and -4). A manually annotated dataset of 1,007 sentences is used for supervised training. The model achieves an F1-score of 92.86% on test data and 88.03% on unseen regulations. Extracted rules are integrated into a BIM compliance checking workflow using SPARQL and IFC-based models, enabling automated, machine-processable regulatory verification.