What is entity?

Example

In a graph, entities are usually represented as nodes. A customer, the order they placed and the product they bought are three entities, so each becomes a node.

Not every entity has to become a node. Some are better stored as a property or a relationship, depending on the questions you want to ask.

In generative AI, "entity" has a narrower meaning: a named person, place or thing that is extracted from unstructured text, for example when building a knowledge graph from documents.

Lessons that use this term

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179 lessons use this term. The 40 with the highest term density are listed here.

Constructing Knowledge Graphs with Neo4j GraphRAG for Python56 mentions

Entity resolutionCustomizationthe entities are identified in the text and subsequently created in the knowledge graph, they may not be18 mentions
Lexical graph configurationCustomizationdefault unstructured graph data model to represent documents, text chunks, and entities3 mentions
LLM configurationCustomizationprompt used for entity extraction and other tasks can also be customized by modifying the prompt_template parameter of the4 mentions
Create a graphKnowledge Graph PipelineExtract entities from the5 mentions
Vector + Cypher retrieverRetrievalA knowledge graph is an organized representation of real-world entities9 mentions
Constructing knowledge graphsIntroductionIdentify the entities in the7 mentions
Chunk sizeKnowledge Graph Pipelinelarger the chunk size, the more context the LLM has when extracting entities and relationships, but it may also lead to less granular3 mentions

Context Graphs: Agent Memory with Neo4j97 mentions

The Long-Term Memory APILong-Term Memorythe previous lesson, you learned how the entity extraction pipeline automatically populates long-term memory from conversation17 mentions
Promote entities to long-term memoryLong-Term Memorytriggers the extraction pipeline, which calls the language model to find the entities in it, then generates an embedding for each5 mentions
The long-term memory schemaLong-Term Memorymemory is necessary — short-term memory disappears at session end, and entities, preferences, and facts need to persist and accumulate across11 mentions
How Messages Connect to Long-Term MemoryShort-Term Memoryhow every message call automatically seeds the long-term memory layer through entity6 mentions
Entity Extraction PipelineLong-Term Memory, the library does more than store the message text — it automatically runs an entity extraction pipeline that connects short-term and long-term9 mentions
The Three Memory TypesIntroduction to Agent Memoryconversation; ephemeral, session-scoped Long-term memory — a persistent entity knowledge graph; survives across sessions Reasoning memory — an audit trail of every tool call and decision;9 mentions
Why graphs over vector embeddingsLong-Term Memorythe previous lesson, you learned how the POLE+O model classifies entities and how relationships carry temporal6 mentions

Building Knowledge Graphs with LLMs75 mentions

Explore the Knowledge GraphExploring your knowledge graphLLM may also extract relationships between the entities, and the graph will hold relationships between the12 mentions
Explore a Knowledge GraphKnowledge graphsknowledge graph maps the relationships between the following entity types referred to in the11 mentions
Benefits and challengesKnowledge graphsKnowledge graphs enhance search capabilities by structuring data into entities and8 mentions
Querying using CypherExploring your knowledge graphinclude the entities and relationships extracted from the28 mentions
How to Construct a Knowledge Graph with an LLMLLM Graph BuilderIdentify the entities in the7 mentions
Customize the schemaLLM Graph Buildercan focus on specific entities and relationships by defining a3 mentions

Graph Data Modeling Fundamentals23 mentions

Extend Your Model with Unstructured DataFrom Domain Graph to Knowledge Grapha report, a support ticket - extend your model with a lexical graph, an entity graph, or1 mention
Lexical and Entity GraphsFrom Domain Graph to Knowledge Graphlexical graph and an entity graph are two ways to bring that content into a11 mentions

Building Neo4j Applications with Spring Data73 mentions

The Application Domain ModelThe Application Domain Modelas classes to create the application domain model, often referred to as entities13 mentions
Spring Data Neo4j ProjectionsCustom Cypher for Read and Writecontain some subset or manipulation of a domain entity and act like a "view" of that9 mentions
Creating Movie classesReading Data from Neo4jmovie data model shows entities for movies, people, and the relationships between5 mentions
Mapping RelationshipsReading Data from Neo4jhave created the application entities for movies and people, but you haven't mapped the most unique part of the graph -6 mentions
Challenge: Create Person repository and controllerReading Data from Neo4jcreate a Person repository interface and controller class to access the person entities in the2 mentions
Mapping Neo4j Object TypesThe Application Domain Modeland Relationships are separate entities in the Neo4j database, and they are also mapped to separate classes in an6 mentions
Challenge: Coffee Shop Modeling ExampleThe Application Domain Modelstyle, different entities, properties/no9 mentions

Neo4j Agent Memory Workshop100 mentions

Entities and RelationshipsLong-term Memoryagent has been writing entities since the short-term module — every add_message in its loop runs44 mentions
Choosing Your ExtractorLong-term Memoryand warm up local models on first run — half a gigabyte before the first entity16 mentions

Build a Knowledge Graph MCP Server Workshop4 mentions

Add Unstructured DataKnowledge Graphsa report, or a support ticket, extend your model with a lexical graph, an entity graph, or1 mention

Agent Memory Workshop with TypeScript41 mentions

What You Just BuiltLong-term Memoryare the circles, and usually represent entities such as people, locations and14 mentions

Agent Memory in 90 Minutes22 mentions

What is Neo4j Agent Memory?Connect Copilot to Your Memoryadds and searches entities and8 mentions

Neo4j and Generative AI Workshop45 mentions

Create a graphKnowledge Graph ConstructionExtract entities from the6 mentions
Chunk sizeKnowledge Graph Constructionlarger the chunk size, the more context the LLM has when extracting entities and relationships, but it may also lead to less granular4 mentions
Constructing knowledge graphsKnowledge Graph ConstructionIdentify the entities in the7 mentions

Modeling and Importing Data into Neo4j Workshop23 mentions

Identifying NodesBuilding Your Graphthis lesson, you will learn how to identify entities that should be nodes and why products are nodes in the Northwind7 mentions

Neo4j & GenerativeAI Fundamentals15 mentions

Creating Knowledge GraphsKnowledge Graphsthe data to an LLM - Extract entities (nodes) and relationships from the5 mentions

Getting Started with Neo4j Document Intelligence28 mentions

Writing the Context PromptBuilding the Graph Modelclinical research or for staff scheduling, and each purpose needs different entities and7 mentions

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