AbstractScope of work requirements (SOWRs) specify the contractual obligations for the contractor to fulfill. Managing the information is crucial to the success of a construction project. This process is, however, often challenging because requirements are typically voluminous and written in an unstructured paper-based format. The current state-of-the-art models are mostly applicable to quantitative constraints for use in automated code compliance checking of design features. This study proposes a novel natural language processing (NLP) framework capable of digitalizing nonquantitative natural language SOWRs outlined in construction contracts. The model includes a comprehensive set of semantic and syntactic rules of linguistic features for extracting contractual work information including actors, actions, objects, constraints, tasks, and obligation. The framework was evaluated on a large textual corpus of provisions of design-build highway contracts. The model yields an impressive precision and recall of more than 93% and 87%, respectively. The proposed system is expected to help the project planner quickly develop an electronic database of contractual work requirements, enabling significantly improved efficiency in project planning and verification.

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