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September 5, 2025Applied SciencesOpen Access

Complex System Diagnostics Using a Knowledge Graph-Informed and Large Language Model-Enhanced Framework

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The framework achieved over 90 percent accuracy in model element extraction, validating its effectiveness.
Knowledge graphs organize system components into a hierarchical structure, aiding in logic-based reasoning.
Large language models automate extraction from unstructured documents, improving user query interpretations.
The approach significantly reduces manual effort in constructing functional models and enhances diagnostic insights.

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Hybrid framework enhances fault diagnosis in high-reliability systems using knowledge graphs and language models.

Marandi et al. (2025) studied this question.

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