Skip to content

Cleanup Dictionnaries - Reduce False Positive #17

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

Open
wants to merge 43 commits into
base: main
Choose a base branch
from

Conversation

Terrtia
Copy link
Contributor

@Terrtia Terrtia commented Apr 9, 2025

Methodology:

graph TD
    A[Language Dictionary] --> A1[Normalize Dictionary<br>Sort and lowercase all entries]
    A1 --> B[Remove words not in kaikki.org dictionary]
    B --> C[Use GlotLID on removed words<br>Re-add if detected language matches]
    C --> D[Remove person/fictional names]
    D --> E[Remove common interjections<br>used in multiple languages]
    E --> F[Remove country names<br>used in multiple languages]
    F --> G[Cleaned Language Dictionary]
Loading

Some names were also present in kaikki.org dictionaries. I manually removed some of them, but some might still remain.

I noticed that the Serbian dictionary isn’t Serbian but Serbo-Croatian

https://kaikki.org/index.html
https://github.com/cisnlp/GlotLID

@pierotofy
Copy link
Member

Hey @Terrtia thanks for the PR. This looks like a good effort. When you mention you've reduced false positives, have you benchmarked the results? Can you share those results and your methodology?

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

Successfully merging this pull request may close these issues.

2 participants