hkgb

To build a GraphRAG knowledge graph from mixed sources, use a schema-guided pipeline that extracts LLM-derived entities from PDFs and bridges them with domain CSV data using a common Document.path key for coherent cross-graph joins.

The best way to integrate LLM-extracted entities with structured domain data in Neo4j is applying a Cypher-based join workflow that bridges lexical graphs from text with domain graphs via a shared Document.path metadata key.

The document-path bridging mechanism connects lexical graphs and domain graphs by using Document.path as a common join key, enabling metadata enrichment and coherent cross-graph relationships across heterogeneous data sources in Neo4j.

Yes, you can configure the SimpleKGPipeline to ingest PDFs and extract lexical entities, then connect the resulting lexical graph to your existing database domain graph using a Cypher-based join workflow in Neo4j.

Yes, an embedding-backed KG builder is required to construct a unified knowledge graph, as it supports the schema-guided extraction pipeline that bridges domain data with lexical graphs extracted from unstructured documents.

Use a hybrid-graph approach for knowledge graph construction when integrating heterogeneous sources like database domain graphs with LLM-derived entities from unstructured PDFs, requiring metadata enrichment and cross-graph joins for GraphRAG enablement.