Embedding Generator

Menu path: Hellixia > Embedding Generator

What it does

Creates semantic embeddings from node names, long names, and comments for downstream semantic analysis.

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

• Semantic proximity learning
• Clustering
• Semantic network construction

Inputs

• Selected nodes
• Node names, long names, or comments

Outputs

• Embedding variables or data suitable for learning and clustering

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 > Embedding 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

• Semantic Variable Clustering
• Automatic Semantic Network Generator