Relationship

Knowledge graph

Shows entities and semantically defined relationships as a typed network.

Diagram
Relationship
Semantic structure

What it answers

How are entities related by meaning?

Shape: Typed entities and labelled links
What it shows: Typed relationships and connection paths.

Example

The question

How are our customers, products and suppliers connected?

A small knowledge graph of business entities and their relationships

Entities as dots, typed by colour, joined by labelled relationships: Order 1043 was placed by Nordia, contains Laptop X1 and was shipped from the Malmö store; Alfa supplies Laptop X1; the Malmö store stocks it.

Illustrative data. It belongs to no company.

When to use it

Use it when

Semantic networks with explicit relationship definitions.

Avoid it when

Unlabelled links or ambiguous entity identity.

How to read it

Read entity types and labelled relationship predicates.

Note

Use stable entity IDs and explicit relationship meanings.

The data you need

Layout: Triple table plus entity table
Fields: SubjectID: text; Predicate: text; ObjectID: text
One row is: One typed relationship between entities. What is the grain?
Rules: Use stable entity IDs and consistent relationship meanings. Identify literal values separately from entity references.
Optional: Entity table: EntityID,Label,Type.
Preparation: Resolve node identities and endpoint joins; define direction and duplicate/self-link handling. Aggregate weights only under a stated relationship or flow definition.
Units: Unweighted links encode presence. Weights need a unit; flow shares divide by stated source, destination or network totals, not an assumed common denominator.

Two linked tables, joined by a shared key column.

Worked example

P1 worksForO1 and O1 locatedInC1. This supports a two-link path, not an automatic assertion thatP1 lives in C1.

SubjectID	Predicate	ObjectID
P1	worksFor	O1
O1	locatedIn	C1

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