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Increasing the LLM Accuracy for Question Answering: Ontologies to the Rescue!
Our previous benchmark research showed that by using a knowledge graph, the accuracy improved from 16% to 54%.
A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases
This study aims to evaluate the accuracy of LLM-powered question answering systems in the context of enterprise questions and SQL databases, while also exploring the role of knowledge graphs in improving accuracy.
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