Why relations matter
An isolated entity is dead information. Once AI knows the chain 'Factory A → makes → Product B → certified to → Cert C → complies with → Standard D', it can include you when answering 'suppliers of Product B compliant with Standard D'.
How to build it
- Internal linking: product ↔ certification ↔ case pages reference each other, forming an on-site graph.
- Structured data: encode relations with Schema.org additionalProperty, certification, brand, etc.
- Synonyms & aliases: cover the variant names buyers use, avoiding 'same-thing-different-name' breaks.
Common mistakes
Putting a certification only as an image, or specs only inside a PDF — that's information for humans but a black box for AI. A graph requires key facts presented as both text and structure.
FAQ
Does a knowledge graph require a graph database?
No. For most B2B sites, on-site structured data + disciplined internal linking + consistent naming already form a 'traversable fact web'. A graph database is a bonus, not a gate.
How does the knowledge graph relate to Layer 1 entity authority?
Entity authority confirms 'who you are'; the knowledge graph confirms 'how you connect to other facts'. Entity first, then relations; together they support the upper citation layers.
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