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Triples

A triple is the fundamental unit of knowledge in Neode. It represents a single fact as three parts:
ComponentDescriptionExample
SubjectThe entity the fact is about”Tesla”
PredicateThe relationship or property”founded_by”
ObjectThe value or related entity”Elon Musk”
This structure follows the RDF standard used in semantic web technologies.

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Object Types

Objects can be one of two types:

Entity

Another entity that can have its own triples. Use for people, companies, places, concepts.
{
  "object": "Elon Musk",
  "object_type": "entity"
}

Literal

A value like a date, number, or text. Use for attributes and properties.
{
  "object": "2003",
  "object_type": "literal"
}

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Confidence Scores

Each triple has a confidence score (0-1) indicating reliability:
  • 0.9-1.0 - Verified facts from authoritative sources
  • 0.7-0.9 - High confidence from reliable sources
  • 0.5-0.7 - Moderate confidence, may need verification
  • <0.5 - Low confidence, treat as uncertain

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Sources

Triples can include a source URL for provenance tracking: 
{
  "subject": "SpaceX",
  "predicate": "founded_year",
  "object": "2002",
  "object_type": "literal",
  "confidence": 0.95,
  "source": "https://en.wikipedia.org/wiki/SpaceX"
}

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Entities

An entity represents a distinct thing in your knowledge graph - a person, company, place, concept, or any noun that can have facts about it.

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Automatic Creation

Entities are automatically created when you store triples. When you create a triple with subject “Tesla”, Neode:
  1. Checks if an entity named “Tesla” exists in your index
  2. Creates a new entity if not found
  3. Links the triple to the entity via subject_entity_id
The same happens for objects with object_type: "entity".

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Entity Disambiguation

Within an index, entity names are disambiguated automatically. If you store triples about “Apple” (the company) and “Apple” (the fruit), they’ll be treated as the same entity unless in different indexes.
Use separate indexes for different domains to avoid entity confusion. For example, one index for “Tech Companies” and another for “Food & Agriculture”.

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Entity Properties

Entities can have:
PropertyDescription
nameThe canonical name
descriptionA text description (can be AI-generated)
avatar_urlAn image URL for display

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Indexes

An index is a namespace for organizing entities and their triples. Think of it as a separate knowledge base or project.

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Why Use Indexes?

  • Separation: Keep different projects isolated
  • Disambiguation: “Apple” in your tech index is different from “Apple” in your food index
  • Access Control: Indexes can be public or private
  • Organization: Group related knowledge together

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Public vs Private

TypeVisibilityUse Case
PrivateOnly you can accessPersonal projects, sensitive data
PublicVisible in ExploreShared knowledge, community resources

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Creating an Index

curl -X POST https://neode.ai/api/indexes \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "name": "Technology Companies",
    "description": "Facts about major tech companies and their products"
  }'

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Graphs

A graph groups related triples together within an index. While indexes separate different knowledge domains, graphs organize triples within a domain.

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Use Cases for Graphs

  • Sessions: Group triples generated in one session
  • Sources: Group triples extracted from the same document
  • Topics: Group triples about a specific topic
  • Versions: Track different versions of knowledge

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Example

# Create a graph for a specific research session
curl -X POST https://neode.ai/api/graphs \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "name": "SpaceX Research - Jan 2026",
    "description": "Facts gathered about SpaceX Starship program",
    "index_id": "YOUR_INDEX_ID"
  }'
Then reference the graph when creating triples: 
{
  "subject": "Starship",
  "predicate": "first_orbital_flight",
  "object": "2025",
  "object_type": "literal",
  "graph_id": "GRAPH_ID",
  "index_id": "INDEX_ID"
}

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Data Model Summary

Index (namespace)
├── Entity (thing)
│   ├── name
│   ├── description
│   └── avatar_url
├── Graph (grouping)
│   └── name, description
└── Triple (fact)
    ├── subject → subject_entity_id
    ├── predicate
    ├── object → object_entity_id (if entity)
    ├── object_type (entity | literal)
    ├── confidence
    ├── source
    └── graph_id (optional)

Ready to Start?

Follow the quickstart guide to create your first knowledge graph.