Regex vs LLM for Structured Text Parsing

A practical decision framework for parsing structured text (quizzes, forms, invoices, documents). The key insight: regex handles 95-98% of cases cheaply and deterministically. Reserve expensive LLM calls for the remaining edge cases.

When to Activate

• Parsing structured text with repeating patterns (questions, forms, tables)
• Deciding between regex and LLM for text extraction
• Building hybrid pipelines that combine both approaches
• Optimizing cost/accuracy tradeoffs in text processing
• Implementing a confidence scorer to identify which extractions fall below an acceptable threshold
• Reducing LLM API costs on document processing pipelines where regex handles the majority of cases
• Processing invoices, receipts, quiz files, or any format where most input follows a predictable pattern

Decision Framework