University of Illinois Urbana-Champaign
Context For my UIUC research project, I worked on SHERPA, a semi-structured RAG framework designed to improve retrieval and reasoning by combining unstructured biomedical text with structured knowledge graphs. Traditional RAG systems rely heavily on vector search over unstructured documents. Our goal was to explore whether adding structured memory through entity-relation extraction and knowledge graph construction could improve retrieval fidelity, reasoning, and answer quality for biomedical question answering. What I Built My contribution focused on two components: query classification and NER / relation extraction for triplet generation. ...