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Knowledge Graphs and LLMs in Action

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Knowledge Graphs and LLMs in Action

By: Alessandro Negro, Vlastimil Kus, Giuseppe Futia, Fabio Montagna
Narrated by: Lisa Farina
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Combine knowledge graphs with LLMs to deliver powerful, reliable, and explainable AI solutions.

Knowledge graphs model relationships between the objects, events, situations, and concepts in your domain so you can readily identify important patterns in your own data and make better decisions. Paired up with LLMs, they promise huge potential for working with structured and unstructured enterprise data, building recommendation systems, developing fraud detection mechanisms, delivering customer service chatbots, or more. This book provides tools and techniques for efficiently organizing data, modeling a knowledge graph, and incorporating KGs into the functioning of LLMs—and vice versa.

In “Knowledge Graphs and LLMs in Action” you will learn how to:

•Model knowledge graphs with an iterative top-down approach based in business needs

•Create a knowledge graph starting from ontologies, taxonomies, and structured data

•Build KGs from unstructured data sources using LLMs

•Use ML algorithms to complete your graphs and derive insights from it

•Reason on the knowledge graph and build KG-powered RAG systems for LLMs

About the technology:
Using knowledge graphs with LLMs reduces hallucinations, enables explainable outputs, and supports better reasoning. By naturally encoding the relationships in your data, KGs help create AI systems that are more reliable and accurate.

About the book:
“Knowledge Graphs and LLMs in Action” shows you how to introduce KGs constructed from structured and unstructured sources into LLM-powered applications and RAG pipelines. Real-world case studies for domain-specific applications illustrate how this powerful pairing works in practice.

About the listener:
For ML and AI engineers, data scientists, and data engineers. Examples in Python.

About the authors:
Alessandro Negro is Chief Scientist at GraphAware and author of “Graph-Powered Machine Learning”. Vlastimil Kůs, Giuseppe Futia, and Fabio Montagna are seasoned ML and AI professionals.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2025 Manning Publications (P)2026 Manning Publications
Computer Science Machine Theory & Artificial Intelligence
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