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Methods for representing diverse information sources as a uniform set of entities and relationships.
Distinct from Knowledge Graph Builders: Focuses on the abstraction and standardization of various sources into a common format, rather than the low-level process of building triples from logs.
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KAG is a graph-augmented retrieval augmented generation system and knowledge graph engine. It functions as a framework that integrates large language models with graph retrieval and numerical calculation to resolve natural language queries. The system creates unified knowledge representations by aligning unstructured data and expert rules through semantic mapping. It maintains mutual indexing between graph structures and original text blocks to ensure that reasoning processes remain linked to verifiable source data. The project provides capabilities for semantic information integration, grap
Provides a standardized knowledge graph abstraction to represent diverse data sources for uniform processing.