A knowledge graph connects entities with named relationships. Instead of storing only “Alice manages the project,” you can represent Alice, the project, and the manages relationship separately. Applications can then ask how people, work, sources, and decisions connect.
Nodes and edges
A node represents an entity or concept. An edge connects two nodes and gives the relationship a name and direction. Properties add details to either one. A connection should represent a meaningful claim, not just the fact that two phrases appeared in the same document.
For example, a project can have an owner, depend on a service, and be supported by a source document. Those are three different relationships and should remain distinguishable.
Ask about time
Relationships change. Minds' bitemporal model distinguishes valid time, when a fact applies in the world, from transaction time, when the store recorded or retired it.
Suppose a project owner changed on Monday, but your system learned about it on Wednesday. Monday is the start of the new real-world relationship. Wednesday is when that information became known to the store. Keeping both helps answer “who owned it then?” and “what did we know at the time?”
Keep the source attached
A graph edge is a claim. Lineage provides a way to inspect its source and derivation. When an answer matters, follow the relationship back to the evidence instead of treating connectivity as truth.
Start with graph operations, then use lineage and learning isolation where your workflow needs review.