Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Analyze Decision Letter Variability to Improve PDF-to-HTML Conversion #4176

Open
meganhicks opened this issue Mar 5, 2025 · 2 comments
Open
Assignees

Comments

@meganhicks
Copy link

meganhicks commented Mar 5, 2025

As a VRO team member working on PDF-to-HTML conversion,
I want to analyze variability in decision letter formatting and text that Gabriel/Ponnia discovered as part of their work in #4134
so that we can understand inconsistencies and ensure our solution dynamically handles variations in structure and content.

Acceptance Criteria:

  • Generate a sample set of decision letters for prototype testing purposes. Samples should include all variability.
  • Analyze variability patterns like missing headers, unexpected line breaks, varying font sizes, or unusual text placement.
  • Flag patterns that could frequently cause misinterpretations during HTML rendering
  • For the patterns, what is the data attached to it and how often does it change?
  • present findings to the team and share with @bianca-rivera
@meganhicks
Copy link
Author

@gabezurita @Ponnia-M can you attach findings to this?

@meganhicks meganhicks changed the title Analyze Decision Letter Anomalies to Improve PDF-to-HTML Conversion Analyze Decision Letter Variability to Improve PDF-to-HTML Conversion Mar 6, 2025
@bianca-rivera
Copy link

From @amylai-va : Investigate variances in rating decisions

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

4 participants