Researchers develop hybrid AI system combining symbolic knowledge engineering with LLMs to organize complex airport operations into machine-readable knowledge graphs

Framework addresses documentation challenges in airport operations caused by technical jargon, regulations, and fragmented communication across multiple stakeholders

Dual-stage approach fuses symbolic Knowledge Engineering with generative Large Language Models to create domain-grounded, semantic knowledge triples

Expert-curated KE structures guide LLM prompts to ensure semantically aligned knowledge discovery and reduce data silos

Methodology evaluated using Google LangExtract library with testing of context window optimization through localized segment-based versus document-level inference

Total Airport Management (TAM) initiative aims to leverage structured knowledge graphs to improve operational coordination and information sharing