Extraction of Activities Information from Construction Contracts Using Natural Language Processing (NLP) Methods to Support Scheduling
Publication: Construction Research Congress 2022
ABSTRACT
Precise extraction of the required activities from contract documents is crucial to develop a complete and accurate construction schedule. Currently, the scheduler is required to read the complete lengthy contract package to extract activities and convert them into a structured format to prepare a schedule. The current manual methods of activities extraction for schedule development are inefficient, laborious, and time-consuming. Although a few researchers have developed models for automated information extraction from legal documents, those models are applicable to quantitative requirements only. To address this, the current study proposes an automated information retrieval system to extract the activities provided in contracts using natural language processing (NLP) methods. The study implemented the dependency parsing technique that employed the syntactic features of requirement text to extract the actors, actions, objects, and conditions specified in the requirement. The model achieved an average recall and precision of 94% and 95%, respectively, on the requirements of a real design-build project. The proposed automated activities retrieval system is expected to help the schedulers develop the construction schedules.
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Construction Research Congress 2022
Pages: 773 - 781
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Published online: Mar 7, 2022
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