ONTOLOGY CONTEXT¶
Queries a named ARC2 RDF triple-store, introspects its OWL classes, object properties, and datatype properties, and serialises a structured JSON summary for use as context by an LLM agent. Use this worker whenever an AI agent needs schema-level awareness of an ontology graph before formulating SPARQL queries or reasoning over its contents.
When to use¶
Tagged: arc2, knowledge-graph, llm-context, ontology, owl, rdf, sparql.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Ontology Store Name | ontology_store_name | text | — | ✓ | Name of the ARC2 RDF triple-store to analyse (e.g. ‘my_model’); the prefix ‘arc2_ontology_’ is prepended automatically if absent. Required — leave blank only if the store does not yet exist and an empty-context fallback is acceptable. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| Ontology Context | context | text | JSON-encoded ontology summary containing detected ontology type, namespace prefix, node types (OWL classes) with instance counts, edge types (object properties) with source/target class pairs and usage counts, and datatype properties; consumed downstream by LLM or agent workers as structured schema context. |
Disciplines¶
- ai_ml.agents
- ai_ml.domain_reasoning
- ai_ml.llm
- platform.ontology
Auto-generated from platform schema. Worker id: ontology_context. Schema hash: 0dad039663c6. Hand-curated docs in workerexamples/ override this page when present.