Drawing Probability Trees by Hand Is Annoying, So I Built This

Description and use

ProbPath automatically converts natural language into a visual probability tree, computes conditional probabilities deterministically, validates the math, and lets users edit and export the result.

Problem

Creating probability trees manually is tedious and error‑prone, especially when the scenario involves conditional probabilities and multiple stages.

Outcome

ProbPath reduces the time to create accurate probability trees, ensures mathematical correctness through deterministic validation, and provides an editable interface that supports iterative refinement.

Workflow

• Describe the probability scenario in natural language
• AI interprets the text into a structured probability model
• Deterministic code calculates all conditional probabilities
• The system validates probability sums and consistency
• A visual probability tree is rendered
• Users can edit nodes, probabilities, or structure
• Recalculation and validation run automatically
• Export the final tree for sharing or documentation

Evidence

Use AI to understand the problem. Use deterministic code to calculate the probabilities.

Source

The system needs to understand the scenario, identify events and outcomes, calculate conditional probabilities, validate the math, position the nodes, and still make the result easy to edit.

Source