Domain Knowledge and Rules Extraction

Extract structured domain knowledge or IF-THEN decision rules from an AI model's training knowledge. Each extraction session appends to a persistent, deduplicated JSONL file scoped by domain name. Adversarial validation is on by default — every answer gets challenged for evidence before it earns a high confidence score.

When to use

• Build a reference knowledge base for your niche domain (one session or many)
• Extract IF-THEN decision rules with specific numeric thresholds
• Stop re-asking the same domain questions every session — persist answers to disk
• Generate adversarially validated entries where each claim is challenged for evidence
• Build training data for fine-tuning downstream models (feeds bdistill-export)

Choosing mode: knowledge vs rules

Use mode: rules when the user needs IF-THEN logic for decision systems, monitoring, or automation. Signal words: "thresholds", "triggers", "rules", "criteria", "limits", "when should I", "at what point", "decision logic", "classification rules".

Use mode: knowledge when the user needs reference material, explanations, or training data. Signal words: "explain", "how does X work", "what is", "knowledge base", "reference", "training data", "Q&A".

When ambiguous, ask: "Do you need structured IF-THEN rules with numeric thresholds (for a decision system or monitoring), or Q&A reference knowledge (for a searchable KB or training data)?"