| derive ontology, suggest ontology, generate ontology, ontology from data, ontology from documents, propose ontology | ontology-derivation | Analyze structured or unstructured data, propose an ontology, and run a human feedback loop before finalizing |
| extract to graph, build graph from data, build knowledge graph, populate graph, extract entities to graph | extract-to-graph | Apply a finalized ontology: extract, deduplicate, and MERGE into the AGE graph |
| entity resolution, context dedup, deduplicate entities, canonicalize entities, merge duplicate entities | context-dedup | Resolve entity aliases using type, graph neighborhood, and source snippet, with scalable blocking and a persistent canonical map |
| apache age, opencypher, cypher(), create_graph, property graph, vertices and edges, MERGE node | opencypher-age-patterns | AGE setup, Cypher wrapping, MATCH/MERGE/CREATE patterns, indexing vertices and edges |
| text to cypher, natural language to cypher, english to cypher, generate cypher, nl to cypher | text-to-cypher | Turning a user question into a validated openCypher query and running it |
| graph schema, list vertex labels, edge labels, ag_label, describe graph | graph-schema-introspection | Discovering labels, edge types, and properties so generated Cypher is grounded |
| visualize graph, vs code graph, render the graph, graph explorer, see the graph, plot the graph, ms-ossdata.vscode-pgsql | text-to-cypher | Generate visualization-ready Cypher (full vertex/edge objects, disp_label, matched AS columns) for the PostgreSQL extension for VS Code graph explorer |
| graph rag, graph augmented, graph augmented retrieval, hybrid graph retrieval | graph-augmented-rag | Retrieval that combines vector similarity with graph traversal and reranking |
| explainability, traceability, provenance, why this recommendation, reasoning path, audit graph answer | graph-explainability | Make facts traceable to sources and recommendations explainable: provenance on vertices and edges, returned reasoning path, weakest link path confidence, and a reproducible reasoning trace log |
| graph semantic search, graph azure_ai embeddings, graph azure openai embeddings, enable azure_ai for graph, configure azure openai for graph | azure-ai-semantic-search | Enable and configure the azure_ai extension, prompt the user for endpoint/key/deployment, and generate embeddings for semantic search |
| cypher example, graph query example, worked graph example | examples | End to end worked examples spanning schema, query, and results |
