For complex business documents -- one approach was to use Named Entity Recognition to identify all entities and use that to build a knowledge graph to serve as

For complex business documents -- one approach was to use Named Entity Recognition to identify all entities and use that to build a knowledge graph to serve as a complementary repository of knowledge (in addition to the vector embeddings of semantic chunks) to aid RAG workflows. Does this proposed approach complement this or supercede the need for NER / Knowledge Graph. Just wondering aloud. Appreciate any insights here.