Knowledge Graphs and LLMs in Action: Build AI systems using connected data
Price: $59.99 - $57.25
(as of Apr 20, 2026 15:37:03 UTC – Details)
Combine knowledge graphs with large language models 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 large language models, 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 knowledge graphs from unstructured data sources using LLMs
• Use machine learning algorithms to complete your graphs and derive insights from it
• Reason on the knowledge graph and build KG-powered RAG systems for LLMs
In Knowledge Graphs and LLMs in Action, you’ll discover the theory of knowledge graphs then put them into practice with LLMs to build working intelligence systems. You’ll learn to create KGs from first principles, go hands-on to develop advisor applications for real-world domains like healthcare and finance, build retrieval augmented generation for LLMs, and more.
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, knowledge graphs help create AI systems that are more reliable and accurate, even for models that have limited domain knowledge.
About the book
Knowledge Graphs and LLMs in Action shows you how to introduce knowledge graphs constructed from structured and unstructured sources into LLM-powered applications and RAG pipelines. Real-world case studies for domain-specific applications—from healthcare to financial crime detection—illustrate how this powerful pairing works in practice. You’ll especially appreciate the expert insights on knowledge representation and reasoning strategies.
What’s inside
• Design knowledge graphs for real-world needs
• Build KGs from structured and unstructured data
• Apply machine learning to enrich, complete, and analyze graphs
• Pair knowledge graphs with RAG systems
About the reader
For ML and AI engineers, data scientists, and data engineers. Examples in Python.
About the author
Alessandro Negro is Chief Scientist at GraphAware and author of Graph-Powered Machine Learning. Vlastimil Kus, Giuseppe Futia, and Fabio Montagna are seasoned ML and AI professionals specializing in Knowledge Graphs, Large Language Models, and Graph Neural Networks.
Table of Contents
Part 1
1 Knowledge graphs and LLMs: A killer combination
2 Intelligent systems: A hybrid approach
Part 2
3 Create your first knowledge graph from ontologies
4 From simple networks to multisource integration
Part 3
5 Extracting domain-specific knowledge from unstructured data
6 Building knowledge graphs with large language models
7 Named entity disambiguation
8 NED with open LLMs and domain ontologies
Part 4
9 Machine learning on knowledge graphs: A primer approach
10 Graph feature engineering: Manual and semiautomated approaches
11 Graph representation learning and graph neural networks
12 Node classification and link prediction with GNNs
Part 5
13 Knowledge graph–powered retrieval-augmented generation
14 Asking a KG questions with natural language
15 Building a QA agent with LangGraph
Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
From the Publisher
“Builds understanding both at a theoretical and a practical level.”
Corey L. Lanum, Visualization Partners
“An excellent introduction to building KG and LLM-powered applications.”
Dave Bechberger, Author of Graph Databases in Action
“Comprehensive and well thought out! The authors hit it out of the park again.”
Sujit Pal, Elsevier
why this book?
Knowledge Graphs and LLMs in Action provides a practical guide to combining structured knowledge graphs with LLMs, showing you how to build, enrich, and exploit graphs in tandem with large language models to gain better context, reasoning, and explainability.
You get hands-on techniques, code, and best practices across all stages—labeling data, modeling the graph, linking to LLM outputs—so you can apply these concepts in real systems.
The synergy helps mitigate common LLM weaknesses—like hallucinations or lack of factual grounding—by anchoring their outputs in explicit relational structure.
about Manning
Manning helps developers and tech professionals stay ahead in a fast-moving industry with expert-led books, videos, and projects. Learning never stops, but it’s hard to keep up, so we focus on content that’s practical, clear, and trusted. As an independent publisher, we adapt quickly, from pioneering early-access books to offering DRM-free eBooks. Our series, like “In Action” and “In a Month of Lunches”, reflect a commitment to making complex topics accessible.
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Level of proficiency
Intermediate Intermediate Intermediate Intermediate Intermediate Advanced
About the reader
Readers need intermediate Python skills and some knowledge of machine learning. For intermediate Python programmers. For intermediate Python programmers. For data scientists and ML engineers. For data scientists and data analysts. For data scientists and machine learning engineers.
Special features
Includes liveBook with out built-in AI assistant. Includes liveBook with out built-in AI assistant. Includes liveBook with out built-in AI assistant. Includes liveBook with out built-in AI assistant. Includes liveBook with out built-in AI assistant. Includes liveBook with out built-in AI assistant.
Pages
368 344 688 456 232 520
Publisher : Manning
Publication date : November 18, 2025
Language : English
Print length : 472 pages
ISBN-10 : 1633439895
ISBN-13 : 978-1633439894
Item Weight : 1.12 pounds
Dimensions : 7.38 x 1.1 x 9.25 inches
Part of series : In Action
Best Sellers Rank: #63,085 in Books (See Top 100 in Books) #11 in Data Processing #23 in Natural Language Processing (Books) #67 in Computer Science (Books)
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