From knowledge graph construction to retrieval-augmented generation: a framework for comprehensive earthquake emergency support

This study proposes a structured framework integrating LLMs with knowledge representation techniques to construct domain-specific knowledge graphs tailored for earthquake emergency scenarios.

The framework extracts entities, relationships, and attributes from unstructured data and employs a knowledge fusion strategy to resolve ambiguities. A comparative experiment demonstrates the effectiveness of the Improved HybridRAG method in generating accurate and coherent responses.