Graph Construction Challenges
The quality of graph construction is crucial for effective retrieval-augmented generation systems, as poor input leads to subpar outputs. While LLMs offer tools for extracting entities and relationships from unstructured text, they face issues with hallucinations and unpredictability. Exciting alternatives like custom machine learning models Rebel and Relic are emerging, providing new avenues for extracting triples without relying solely on LLMs.In this clip
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Practical AI
GraphRAG (beyond the hype)
Related Questions
Can you help me with suggesting particular paths for building and populating a Knowledge Graph using LLMs that includes time-dependent data (such as retrieving the 'current' President of the USA and previous presidents) for Retrieval Augmented Generation (RAG) to help with business goals or more advanced User Interfaces (UIs)?
Can you help me with suggesting particular paths for building and populating a Knowledge Graph using LLMs that includes time-dependent data, such as retrieving the 'current' President of the USA and previous presidents? I want to use this Knowledge Graph for Retrieval Augmented Generation (RAG) to help with business goals or in more advanced User Interfaces (UIs).
Can you help me with suggesting particular paths for building and populating a Knowledge Graph that includes time-dependent data, such as retrieving the 'current' President of the USA and previous presidents, using LLMs? I want to use this Knowledge Graph for Retrieval Augmented Generation (RAG) to help with business goals and possibly integrate it with more advanced User Interfaces (UIs).