Construction contract risk identification based on knowledge-augmented language model

Construction contracts are the foundation for relationships among project stakeholders, protecting their rights and interests throughout the project's lifespan. Contractual risks remain a long-standing and significant concern for all parties involved in a construction project, and failure to identify these risks in the contract clauses may result in disputes, posing a risk of project loss. According to a recent report (Victoria et al., 2022), the global average values and durations of disputes are $52.6M and 15.4 months, respectively. Contract review involves several important tasks, such as identifying and modifying ambiguous clauses (Artan Ilter and Bakioglu, 2018), clarifying vaguely stated requirements (Hassan and Le, 2020; ul Hassan et al., 2020; ul Hassan and Le, 2021), and correcting inaccurately referenced specifications (Hamie and Abdul-Malak, 2018). Currently, the construction industry mainly relies on manual review due to the lack of sophisticated and reliable automated methods for identifying construction contract risks (CCRI). However, studies (Lee et al., 2019; Moon et al., 2021) have shown that this labor-intensive approach is error-prone and time-consuming.