Unstructured-IO / Unstructured-IO/unstructured
[Feature Request] Add document layout analysis confidence scores
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Description
Feature Description
Include confidence scores for each extracted element to help downstream processing decide which elements to trust.
Use Case
In our enterprise RAG pipeline, we process thousands of PDFs daily. Some elements are extracted with low confidence (rotated tables, scanned handwritten notes). Having confidence scores would let us:
- Filter out low-confidence extractions
- Route uncertain elements to manual review
- Weight chunk importance in retrieval
Current Behavior
All extracted elements are treated equally regardless of extraction quality.
Proposed Enhancement
element.metadata.confidence_score # 0.0 - 1.0
element.metadata.extraction_method # 'ocr', 'native', 'inferred'
This would significantly improve RAG quality for noisy document sources. Thank you!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no implementation files, tests, or entry points. Start by locating the element metadata and document-layout extraction path, then determine how confidence_score and extraction_method should be produced; done means each extracted element exposes the proposed metadata with the stated score range and method values.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100