DefinedTerm Schema

DefinedTerm is a schema.org type that marks up a single glossary definition as a discrete, machine-readable entity — a name, a description, and a pointer back to the set it belongs to. It's built for exactly the kind of page this is: a term, a definition, nothing ambiguous about where one ends and the next begins.

{
  "@type": "DefinedTerm",
  "name": "AI Overview",
  "description": "An AI-generated text summary produced by Google's Gemini model that appears at the top of Search results for queries where Google determines an AI answer adds value.",
  "inDefinedTermSet": {
    "@type": "DefinedTermSet",
    "name": "Angryturtle AI Search Glossary"
  }
}

How AI systems use it

Definitional queries — "what is X", "define X", "X meaning" — are some of the most common prompts sent to AI search tools. When an AI engine encounters a DefinedTerm block, it doesn't have to parse a paragraph and guess where the definition starts and stops. The name field and description field are already separated out. That's a small difference in structure but it changes how confidently an AI system will quote the page, because there's no interpretation step between the markup and the answer.

DefinedTermSet is the wrapper around the whole glossary. It tells search engines and AI crawlers "these 180-odd terms belong together, and this site owns the set." When an AI system cites one definition from inside that set, the attribution generally goes to the set's owner — in this case, Angryturtle.

DefinedTerm vs a plain definition paragraph

A well-written definition paragraph can still get picked up by an AI Overview or a featured snippet — Google's extraction isn't limited to structured data. What DefinedTerm adds is certainty. Prose extraction depends on the AI correctly identifying which sentence is the definition versus which sentence is context, an example, or a caveat. DefinedTerm removes that guesswork, which matters most on longer glossary pages where the definition is one paragraph among several.

Common mistakes

The most common error is writing a DefinedTerm description that's too long or too vague to actually quote — a two-sentence marketing description instead of one specific, standalone sentence that answers the "what is X" query directly. Another is forgetting to nest every term under the same DefinedTermSet, which breaks the "this is a coherent glossary" signal and makes each term look like an orphaned fragment instead of part of an authoritative collection.

India context: Definitional content covering AI search terms, local SEO terminology, and India-specific concepts across healthcare, real estate, and education is high-value AEO content — it's the kind of query B2B buyers and marketing teams type when they're researching a vendor or a tactic, and Indian competitors have largely not implemented DefinedTerm schema on their glossary content yet.

Example

Angryturtle's glossary page for "Share of AI Voice" uses DefinedTerm schema. When a user asks Perplexity "what is share of AI voice?", Perplexity may cite the Angryturtle glossary definition directly, with a link back — an LLM citation driven specifically by the DefinedTerm markup rather than by prose extraction.

Related schema and pages

DefinedTerm sits alongside FAQPage and QAPage as the three schema types that most directly serve AEO — all three exist to give an AI system a pre-structured question-and-answer or term-and-definition pair instead of a paragraph to interpret. On a glossary hub, DefinedTerm does the heavy lifting for the term pages themselves, while FAQPage handles any FAQ sections layered on top.

Related terms: Structured Data → · Schema.org → · FAQPage schema → · QAPage schema → · AEO Glossary hub → · Answer Engine Optimization → · AEO Services → · AI Overview →