International Conference on Technology Innovations for Crisis Management [ICTICM]

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Author: search.filters.author.De Silva, L.D.R.E.Subject: search.filters.subject.crisis management

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    Large Language Model Pipelines for Crisis Intelligence: Automated Help Request Classifier
    (Sri Lanka Institute of Information Technology, 2026-05-21) De Silva, L.D.R.E.
    This research examines the development and deployment of a Crisis Intelligence Pipeline, engineered to address the catastrophic information surge following Cyclonic Storm Ditwah in Sri Lanka [1]. The system integrates advanced prompt engineering methodologies, specifically few-shot learning, Chain-of-Thought [2], and Tree-of-Thoughts [3] to transform unstructured humanitarian data into actionable logistics strategies. Through rigorous stability testing under varying temperature gradients, the study identifies a "Safe Mode" for deterministic triage and a "Chaos Mode" that highlights the risks of model hallucination in high-stakes environments. Furthermore, the pipeline utilizes Pydantic-based schema validation [4] and token economics [5] to ensure scalability and cost-efficiency. Results indicate that structured reasoning architectures significantly enhance the precision of resource allocation and signal-to-noise discrimination, providing a vital technological framework.