Biomedical knowledge-graph QA stops relying on document retrieval alone: three systems run in parallel and merge, lifting satisfaction from 36% to 86%
After GeneNetwork's 1TB structured database was remodeled as an RDF graph alongside a literature corpus, a system that runs document, graph and agentic retrieval-augmented generation in parallel and merges their answers raised the satisfaction rate from 36% for plain document retrieval to 86% on 40 expert questions, while delegating most work to a local model still reached 59%.