From the course: Knowledge Graph Data Engineering for Generative AI Use Cases
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Thinking about nodes - Neo4j Tutorial
From the course: Knowledge Graph Data Engineering for Generative AI Use Cases
Thinking about nodes
- [Instructor] In a graph data model, nodes are the circles or dots in a knowledge graph. They are what you connect together with relationships to make a triple. Looking at relational data, these nodes are normally going to be named entities. A named entity does not mean it is a personal or business name. It means it is a named thing in the world. So, in our example, this could be olive oil, a state in an address, or the first name of a customer. These are things in the world, and they have names. These named entities usually have at least an ID and a label in the data model, but many have additional attributes like a customer's address. For instance, which specific customer purchased a specific product for a specific purchase order. Those are all named entities. Those are all nodes. Having a node that captures all the instances, those specific customers and products and purchase orders, are what the node contains. The node gives your LLM a smaller set of entities to disambiguate and…
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