Скачать или смотреть Implementing Knowledge Graph Quality Assessment | Panos Alexopoulos | Connected Data London 2025

The rapid rise of Graph Retrieval-Augmented Generation (Graph RAG) has introduced an innovative approach to grounding Large Language Models (LLMs) with factual information from knowledge graphs (KGs). This is an approach that has gained significant traction due to its ability to enhance the factual accuracy and contextual relevance of LLM outputs better than document-based RAG.

However, many of the knowledge graphs employed in Graph RAG applications are automatically constructed using LLM-based techniques and, quite often, lack the necessary accuracy, completeness, and consistency for reliable knowledge grounding.

This masterclass focuses on the critical issue of knowledge graph quality for Graph RAG applications and will teach participants practical methods and techniques for assessing graph quality and identifying gaps and inaccuracies that prevent them from better supporting LLMs in generating accurate and reliable responses.

Link to full Masterclass: https://2024.connected-data.london/ta...

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Panos Alexopoulos. Founder and Principal Educator, OWLTECH

Panos Alexopoulos has been working in the field of Data Semantics and AI since 2006. He has published more than 60 academic papers in the field, and he is the author of the O’Reilly book “Semantic Modeling for Data – Avoiding Pitfalls and Breaking Dilemmas".

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