WebMEM™

The Protocol for Structuring, Delivering, and Conditioning Trust-Scored AI Memory on the Open Web

Turtle (TTL)

Turtle (TTL) is a compact, machine-readable format for expressing semantic triples—used in AI retrieval and memory systems to store and retrieve structured relationships between entities, concepts, and claims.

🧠 Full Definition

Turtle, short for Terse RDF Triple Language, is a W3C standard syntax for encoding subject–predicate–object statements about entities. These triples form the foundation of semantic web graphs, linked data, and AI memory graphs.

📜 Role in the WebMEM Protocol

In the WebMEM Protocol, TTL is one of the core output formats in Semantic Digests. It is used to:

  • Express facts, relationships, and citations as RDF triples
  • Enable AI systems to store, recall, and reason over structured content
  • Feed directly into retrieval graphs, trust graphs, and model context pipelines

⚙️ How It Works

TTL uses the RDF triple model in the format:

<subject> <predicate> <object> .

Example:

<https://webmem.com/glossary/trust-architecture> a schema:DefinedTerm ;
    schema:description "Trust Architecture is the framework that enables..." ;
    schema:isPartOf <https://webmem.com/glossary/definedterm-set> .

TTL endpoints are typically published at: /semantic/ttl/

💡 Example Use Case

A glossary page on Retrievability might include:

  • A DefinedTerm block for human + schema visibility
  • A JSON-LD schema object
  • A TTL version of the same facts, citations, and relationships

AI systems ingest the TTL file, store the triples, and integrate them into memory and retrieval layers.

🔍 Why It Matters

  • Provides a compact, standards-based way to express relationships
  • Strengthens your Trust Graph by making edges explicit
  • Improves semantic persistence and retrievability in AI agents

🗣️ In Speech

“Turtle is the format that tells AI exactly how your facts connect—like a blueprint for your content’s memory graph.”

🔗 Related Terms