Causal Semantic Diagram Generator

Menu path: Hellixia > Document Analysis > Causal Semantic Diagram Generator

What it does

Connects key semantic concepts extracted from text according to causal relationships.

Treat Hellixia output as a structured starting point for analyst review, expert refinement, learning, inference, or communication. Generated causal directions and quantification should be checked before they are used operationally.

When to use it

• Causal narratives
• Mechanism extraction
• Pre-Bayesian causal mapping

Inputs

• Knowledge File content
• Optional selected node name, long name, or comment

Outputs

• Causal Semantic Diagram

Step-by-Step Workflow

1. Prepare the network, source material, selected nodes, selected arcs, or Knowledge Files required by the function.
2. Confirm that Hellixia provider settings and model access are configured.
3. Open Hellixia > Document Analysis > Causal Semantic Diagram Generator.
4. Review the available options and add General Context when the model needs domain-specific guidance.
5. Run the function and inspect the generated graph, comments, priors, embeddings, translations, or images.
6. Edit the output in BayesiaLab before using it for analysis, publication, or decision support.

Review Guidance

Check whether the generated labels, relationships, comments, classes, probabilities, or causal effects match the source material and expert understanding. For causal outputs, verify that the proposed direction and mechanism are plausible and that no important confounder or alternative explanation has been hidden by the generated structure.

Related Functions

• Causal Network Generator
• Semantic Flowchart Generator

Examples

• Cinema — Semantic Network or Causal Semantic Diagram