Glossary

Technical terms and TrustGraph-specific terminology including knowledge cores, semantic relationships, and graph-based concepts.

28 terms available

C

Collections (TrustGraph)

Logical groupings of related data in TrustGraph, allowing organization and isolation of documents, entities, and relationships into manageable sets.

TrustGraph Concepts

Containers

Lightweight, portable packages containing an application and all its dependencies, providing consistent runtime environments across different systems.

Infrastructure

Context Graphs

Knowledge graphs specifically optimized for AI model consumption, engineered to provide LLMs with structured, semantically rich context that reduces hallucinations and improves reasoning accuracy.

Core Concepts

Cypher/GQL

Cypher is Neo4j's graph query language; GQL is the emerging ISO standard for graph queries, based on Cypher. Both use ASCII-art syntax for pattern matching.

Infrastructure

E

Embeddings

Dense vector representations of data (text, images, etc.) that capture semantic meaning in a numerical format suitable for machine learning.

Core Concepts

F

Flow Classes (TrustGraph)

Templates or blueprints for TrustGraph flows, defining reusable processing pipelines that can be instantiated with different configurations.

TrustGraph Concepts

Flows (TrustGraph)

TrustGraph's term for processing pipelines - sequences of operations that transform data as it moves through the system, from ingestion to knowledge graph construction.

TrustGraph Concepts

G

GraphQL

A query language for APIs that allows clients to request exactly the data they need, not related to graph databases despite the name.

Infrastructure

GraphRAG

Graph-based Retrieval-Augmented Generation that combines Knowledge Graphs with vector search for more accurate, relationship-aware AI responses.

Core Concepts

K

Knowledge Cores (TrustGraph)

TrustGraph's modular, swappable Knowledge Graph instances, allowing different graph databases or configurations to be used interchangeably based on requirements.

TrustGraph Concepts

Knowledge Graph

A structured representation of knowledge as a network of entities (nodes) and their relationships (edges), enabling machines to understand and reason over interconnected information.

Core Concepts

M

MCP (Model Context Protocol)

An open protocol for connecting AI models to external data sources and tools, enabling LLMs to access real-time information and perform actions.

Infrastructure

Multi-Tenant

A software architecture where a single instance of an application serves multiple customers (tenants), with data isolation ensuring each tenant's data remains separate and secure.

Infrastructure

O

Ontology

A formal specification of concepts, relationships, and rules within a domain, defining what exists and how things relate in a knowledge domain.

Core Concepts

A Retrieval-Augmented Generation technique that uses formal ontologies (OWL schemas) to guide the extraction of structured, typed knowledge from unstructured text, producing conformant Knowledge Graphs with validated entity types and relationships.

Core Concepts

OWL (Web Ontology Language)

A W3C standard for defining formal ontologies with rich semantics, constraints, and reasoning capabilities built on RDF, enabling automated inference and validation.

Standards

P

Property Graph

A graph data model where both nodes and relationships can have properties (key-value pairs), commonly used in modern graph databases like Neo4j and TrustGraph.

Core Concepts

Pub/Sub (Publish-Subscribe)

A messaging pattern where publishers send messages to topics, and subscribers receive messages from topics they're interested in, enabling decoupled, asynchronous communication.

Infrastructure

R

RAG

Retrieval-Augmented Generation - A technique that enhances language models by retrieving relevant information from a knowledge base before generating responses.

Core Concepts

RDF (Resource Description Framework)

A W3C standard for representing information as subject-predicate-object triples, enabling machine-readable data exchange and semantic web applications.

Standards

S

Schema

A formal definition of the structure, constraints, and organization of data, defining what entity types, properties, and relationships are allowed in a system.

Core Concepts

Semantic Web

A vision of the Web where data is machine-readable and interlinked through standardized formats, enabling automated reasoning and knowledge sharing across systems.

Core Concepts

SKOS (Simple Knowledge Organization System)

A W3C standard for representing taxonomies, thesauri, classification schemes, and controlled vocabularies using RDF, enabling semantic interoperability across knowledge organization systems.

Standards