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Daneel AI

How to Build a Knowledge Graph

The knowledge graph feature extracts named entities (people, organizations, places, concepts) from your vault documents and builds an interactive 3D visualization of their relationships.

Prerequisites

Section titled “Prerequisites”
  • A document vault with at least one imported document
  • Enough free memory for the NER model (183 MB–583 MB depending on model choice)

Enable the knowledge graph

Section titled “Enable the knowledge graph”
  1. Open the vault overlay and select your vault.
  2. Click the Knowledge Graph toggle to enable it.
  3. Daneel downloads the NER (Named Entity Recognition) model if not already cached, then processes all documents in the vault.

Entity extraction runs locally in a dedicated web worker using GLiNER (an ONNX model). No data leaves your browser.

Choose a NER model

Section titled “Choose a NER model”

Open Settings > Knowledge Graph to select a model:

ModelSizeLanguagesNotes
GLiNER Small v2.1 (fp32)583 MBEnglishHighest accuracy
GLiNER Small v2.1 (int8)183 MBEnglishGood balance of size and quality
GLiNER Multi v2.1 (int8)349 MBMultilingualFor non-English documents
GLiNER Multi v2.1 (fp16)580 MBMultilingualHighest multilingual accuracy

The int8 English model is a good default for most use cases.

Pick an ontology preset

Section titled “Pick an ontology preset”

Ontology presets define what types of entities Daneel looks for. Choose one in Settings > Knowledge Graph:

  • General — people, organizations, places, events, concepts
  • Academic — researchers, institutions, theories, publications
  • Legal — cases, statutes, courts, parties
  • Medical — conditions, treatments, drugs, anatomy
  • Programming — languages, frameworks, APIs, data structures
  • Business — companies, products, markets, financials
  • Travel — destinations, landmarks, transport, accommodations
  • History — historical figures, battles, treaties, eras

You can also define a custom ontology by entering your own entity type labels.

Explore the visualization

Section titled “Explore the visualization”

Once extraction completes, the knowledge graph appears as a 3D interactive visualization:

  • Nodes represent entities, sized by how often they appear
  • Edges represent co-occurrence relationships between entities
  • Colors indicate entity types (people in blue, organizations in green, places in red, etc.)
  • Hover over a node to see its label and type
  • Click a node to focus on its neighborhood and trigger a Wikipedia lookup
  • Click and drag to rotate the view
  • Scroll to zoom in and out

For analytics, path finding, sizing modes, topic clusters, and the Wikipedia lookup, see How to Explore Your Knowledge Graph.

Customize the visualization

Section titled “Customize the visualization”

In Settings > Knowledge Graph, adjust:

  • Particle animation — toggle animated particles along edges
  • Bloom glow — toggle a glow effect on nodes
  • Charge strength — how strongly nodes repel each other (affects spacing)
  • Link opacity — transparency of relationship edges
  • Node scale — base size multiplier for nodes

How entity resolution works

Section titled “How entity resolution works”

Daneel automatically deduplicates entities using normalized string matching with a configurable threshold (default: 85% similarity). “OpenAI”, “Open AI”, and “OPENAI” resolve to a single entity. Adjust the deduplication threshold in settings if you need stricter or looser matching.

Next steps

Section titled “Next steps”