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March 30, 2026Journal of Legal Affairs and Dispute Resolution in Engineering and Construction

Integration of a Natural Language Processing and Project Scheduling Tool for Contractual Delay Risk Identification in a Highway Construction Project Using LLMs

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Authors

GMGaureeshwar MandaAVAneetha Vilventhan

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Overview

Framework integrates NLP and project scheduling to enhance model performance in identifying contractual delay risks.

Key Points

  • To develop an automated framework for identifying contractual delay terms related to scheduling delays in construction projects.
  • Integrated natural language processing with project scheduling tools and large language models.
  • Applied the framework in a case study to evaluate its functionality.
  • Utilized K-fold cross validation for model performance validation.
  • Achieved model performance metrics with training loss of 0.34 and validation loss of 0.359.
  • Attained training token-level accuracy of 92.69% and validation accuracy of 91.87%.
  • The framework supports efficient identification of contractual delay risks, reducing manual analysis efforts.

Cite This Study

Manda et al. (2026) studied this question.

synapsesocial.com/papers/69c9c5e2f8fdd13afe0bdf6chttps://doi.org/10.1061/jladah.ladr-1500
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