The Data Exchange with Ben Lorica
Knowledge Graphs: Contextualizing Enterprise Data for More Accurate LLMs
Dec 21, 2023
Knowledge graph experts from data.world discuss their work on using knowledge graphs to improve the accuracy of language models for question answering on structured SQL databases. They explain the creation of a knowledge graph from a data warehouse, evaluate the effectiveness of knowledge graphs in improving question answering accuracy, and discuss how to convince organizations to adopt knowledge graphs for improved data exploration. They also highlight the benefits of knowledge graphs, compare RDF and property graphs, and emphasize the importance of improving knowledge graph accuracy and combining knowledge graphs with vector databases.
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Quick takeaways
- Investing in knowledge graphs can improve accuracy and performance of natural language interfaces over SQL databases.
- Knowledge graphs enhance the accuracy of large language models in answering complex questions over SQL databases.
Deep dives
Investing in Knowledge Graphs for Question Answering on SQL Databases
This podcast episode explores the role of knowledge graphs in question answering on large language models (LLMs) for enterprise SQL databases. The motivation behind the study is the excitement around LLMs and chat interfaces, but with a focus on structured SQL data. The current text-to-SQL approaches have limitations and are mainly based on small data samples. The hypothesis is that knowledge graph semantics can bridge the gap between technical infrastructure and the needs of businesses. The podcast episode discusses the importance of investing in knowledge graphs for higher accuracy and improved performance in natural language interfaces over SQL databases.
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