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BayesiaLabBayesiaLab User GuideMenusHellixiaDocument AnalysisKnowledge Graph Generator

Knowledge Graph Generator

Context

A Knowledge Graph is a structured representation of information that captures the relationships between entities such as concepts, people, and organizations. In this representation, Nodes represent entities and Arcs represent the semantic relationships between them.

The relationship types include seven families:

  • Taxonomic (“is-a”)
  • Partitive (“part-of”)
  • Attributive (“has-property”)
  • Causal (“causes” or “influences”)
  • Functional (“used-for” or “enables”)
  • Temporal (“occurs-before” or “results-in”)
  • Spatial (“located-in” or “next-to”)

Function Overview

The Knowledge Graph Generator is a Hellixia feature that builds a complete Knowledge Graph from scratch using Large Language Models. It extracts both the nodes (entities) and the semantic relationships between them entirely from the knowledge encoded in LLMs, without requiring you to supply any nodes beforehand.

Available Knowledge Graph Generators

Menus > Hellixia > Document Analysis > Knowledge Graph Generator, which builds the graph using a Knowledge File as the central element, grounding the output in a supplied document rather than purely in the LLM’s internal knowledge.

Menus > Hellixia > Semantic Knowledge Graph Generator, which requires a node as a starting point, with an optional knowledge file.

Examples

Version Notes

Available in BayesiaLab 11.6 and later.

Causal Semantic Diagram GeneratorPropositional Causal Bayesian Network Generator