Knowledge Graph
The Knowledge Graph is Baan’s view into the conceptual structure of your content. It can extract entities (people, organizations, places, concepts, events, products, creative works) from published articles, link them to Wikidata IDs, and render the result as an interactive graph.
This is a rare CMS combination: entity extraction, Wikidata disambiguation, graph visualization, and AI-driven article suggestion in a single tool.
Entity Extraction
Section titled “Entity Extraction”When entity extraction runs, Baan asks the configured AI provider to identify named entities and classify them into one of seven types:
| Type | Examples |
|---|---|
| Person | Steve Jobs, Ada Lovelace |
| Organization | Vercel, OpenAI |
| Place | Tokyo, Silicon Valley |
| Concept | Server Components, Functional Programming |
| Event | WWDC, Apollo 11 |
| Product | Next.js, Claude Code |
| CreativeWork | Books, films, papers |
Extracted entities are stored in the post’s frontmatter and indexed in the article_index.entities column for fast graph queries.
Wikidata Linking
Section titled “Wikidata Linking”The same name can mean different things in different contexts. “Apple” might be the fruit or the company; “Java” might be the language or the island. Baan can resolve this ambiguity by attaching a Wikidata ID to entities:
Apple(the company) →Q312Apple(the fruit) →Q89Java(the language) →Q251Java(the island) →Q3757
Two articles that mention “Apple” in the company sense are linked in the graph; an article about apples (fruit) is not. This drastically reduces false connections.
The Wikidata ID is also emitted in the article’s JSON-LD mentions and about properties, helping AI engines and search crawlers correctly identify what the article is about.
The Graph View
Section titled “The Graph View”Every extracted entity becomes a node. Articles that share an entity are linked. The graph is interactive — pan, zoom, click a node to see all articles tagged with it.
The visualization makes content gaps visible at a glance:
- A dense
Next.js × Reactcluster suggests strong coverage of frontend topics - An isolated
UI Designnode suggests you’ve mentioned it but never written deeply about it - A heavy
Vercelnode next to a thinAWSnode reveals which platforms you’ve actually engaged with
Bridge Article Generator
Section titled “Bridge Article Generator”Select two entities on the graph. The Bridge Article Generator prompts the AI to produce 5 article ideas that connect those two entities, each with:
- A working title
- The angle / hook
- A complete outline
Click “Create Post” to land in the editor with the title, entities (already in frontmatter), and outline pre-filled. You write the body — the structural work is done.
This turns the Knowledge Graph from a passive visualization into an active content discovery tool. Instead of staring at a blank page, you start from “what can I write that bridges A and B?”.
Implementation Notes
Section titled “Implementation Notes”- Entity extraction runs on the configured AI provider (Anthropic / OpenAI / Gemini). Set the provider under Settings → AI.
- Existing articles can be re-indexed in bulk via the Settings UI or
POST /api/cms/v1/index/sync. - The full spec lives at
docs/spec/knowledge-graph.mdin the source repository.