RDF
Also called: resource description framework, rdf data model
RDF (Resource Description Framework) is a W3C standard data model that expresses information as triples: a subject, a predicate, and an object, each named by a global identifier (IRI). It represents entities and their relationships as a graph, and it underpins knowledge graphs, linked data, and JSON-LD structured data.
The atomic unit of RDF is the triple: subject, predicate, object. Read one like a tiny sentence. “SEOBRO (subject) is a (predicate) SEO agency (object).” Any of the three slots can be named by an IRI, a global identifier, so two different systems can agree they mean the same thing.
You almost never hand-write raw RDF. It has several interchangeable text formats, called serializations: Turtle, N-Triples, RDF/XML, RDFa, and JSON-LD. The one that matters for SEO is JSON-LD, which Google recommends for structured data. Every schema.org block you ship as JSON-LD is RDF underneath, so the triple model tells you what your markup is actually saying to a machine.
<https://seobro.com> a schema:Organization ;
schema:sameAs <https://www.wikidata.org/entity/...> .Why it matters for AI search
Google’s Knowledge Graph, Wikidata, and the entity layers behind AI Overviews, ChatGPT, and Perplexity all store facts as triples. When you connect your entities to known nodes (for example sameAs pointing to a Wikidata or Wikipedia URL), you help engines resolve exactly who and what your pages describe instead of guessing.
On versions: RDF 1.1 (2014) is the standing W3C Recommendation. A 1.2 revision that adds triple terms (sometimes called RDF-star) is in progress as of 2026, so treat any 1.2-specific detail as not yet final.
How it affects your traffic
AI answer engines quote sources they can parse cleanly into entities and facts. When your JSON-LD spells out relationships (organization, author, product, and sameAs links to knowledge-graph nodes), you hand AI Overviews, ChatGPT, and Perplexity ready-made triples to lift, which is how a brand gets named in an answer instead of buried under it. Missing or ambiguous markup leaves machines to infer, and they often infer wrong or skip the page. Our AI SEO work maps your entities and ships structured data that resolves to known nodes, so answer engines can cite you with confidence.
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