From Noisy Documents to Structured Data

Project overview

Modular extraction for receipts and noisy documents, with validation and human review designed into the pipeline.

Problem

OCR output is noisy, layouts vary and plausible extraction errors can pass unnoticed.

Constraints

• Uncertain OCR
• Changing document layouts
• Need for traceable corrections
• Human review capacity

Architecture or approach

Modular OCR, layout interpretation, field extraction, normalization, confidence-aware validation and review queues.

Key engineering decisions

• Keep extraction stages replaceable
• Validate meaning, not only syntax
• Escalate uncertainty instead of hiding it

Trade-offs

More modular stages create orchestration overhead but make failures diagnosable.

Outcome or current status

Validated prototype and production-reliability research; no deployment-scale claim is made.

Lessons learned

The difficult problem is not extracting a value once; it is knowing when not to trust it.

What I would improve next

Broaden evaluation sets and strengthen error taxonomy.