Querying using Cypher

The graph generated by an LLMA model trained on text to predict the next token, and so to generate language. may not conform to a strict schema (depending on how you configured the LLM). The lack of a strict schema changes how you query the graph. You may not be looking to find a specific nodeA vertex in a graph. In a property graph it can carry labels and properties. or relationshipA named, directed connection between two nodes. Every relationship has a type, a start node and an end node., but rather a pattern or structure in the graph.

In this lesson, you will explore examples of how to query a knowledge graphA representation of real-world entities and their relationships, stored according to organizing principles, typically in a graph database. using CypherNeo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it..