Integrating semantic NLP and logic reasoning into a unified system for fully-automated code checking

Abstract

Existing automated compliance checking (ACC) systems are limited in their automation; they rely on the use of hard-coded, proprietary rules for representing regulatory requirements, which requires major manual effort in extracting regulatory information from textual regulatory documents and coding these information into a rule format. To address this limitation, this paper proposes a new unified ACC system that integrates: (1) semantic natural language processing techniques and EXPRESS data-based techniques to automatically extract and transform both regulatory information (in regulatory documents) and design information [in building information models (BIMs)] for automated compliance reasoning, and (2) semantic logic-based information representation so that the reasoning could be fully automated. To test the proposed system, a BIM test case was checked for compliance with Chapter 19 of the International Building Code 2009. Comparing to a manually-developed gold standard, 98.7% recall and 87.6% precision in noncompliance detection were achieved.