The system retrieves information through a graph and provides the relevant material to a model. It can combine graph traversal with text or vector search to support questions about connected records.
Graph construction and query accuracy are critical. Incorrect extraction, duplicate ingestion or unsuitable queries can produce wrong context even when the final response sounds confident.
ELI5
This approach gives AI information by following connections in a map of records. The model then uses the retrieved material when producing its answer.
For example, an assistant asked which projects used a particular dataset can follow dataset-to-paper and paper-to-project links. It should show supporting records and verify that repeated imports have not inflated the results.
Is graph retrieval always better than vector search?
No. Their strengths differ, and the best choice depends on the questions, data quality and measured results.
Can graph construction introduce errors?
Yes. Misidentified entities, missing links and duplicates can affect every answer built on the graph.
