Integrating Natural Language Processing with 4D BIM: A Review and Thematic Synthesis

This paper explores the integration of Natural Language Processing (NLP) and 4D Building Information Modeling (BIM). The integration of knowledge disciplines facilitates the emergence of new trends. One form of this integration is the use of artificial intelligence (AI). Recently, the BIM literature has expanded with the application of AI technology. However, AI and BIM are broad domains, and each of them encompasses multiple sub-domains. NLP, a well-established sub-domain of AI, enables computers to understand and communicate using human language. Conversely, 4D BIM is a specific area within BIM that facilitates the integration of BIM models with construction schedules. While existing literature explores the integration of each sub-domain with other major fields—such as the interplay between NLP and BIM and the connection between 4D BIM and AI—a significant gap remains in integrating the two sub-domains of NLP and 4D BIM. To provide state-of-the-art research for this integration, this paper presents a review to investigate the building blocks of both chains. This review aims to evaluate the literature, synthesize information, and identify potential research gaps. It uses a qualitative research methodology to facilitate a thorough examination of data from 122 articles. This supports the identification of 72 topics, eight 4D BIM themes, and five NLP themes. © 2025 Elsevier B.V., All rights reserved.