Research: Aligning substantially abridged text
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- Dominant language
- Python
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- 39
- Forks
- 7
- Avg merge
- 1d 9h
- Merged PRs (30d)
- 5
Description
Peeled off from sillsdev/silnlp#250
Aligning substantially paraphrased or abridged texts
- This really needs lexicographic information in either alignments, cognates or a dictionary of shared words
- Some papers that could help are: yasa or champollion
- Both Bloom and Scripture will be well aligned data. Non-scripture text that is doing substantial abridgment is beyond the scope of Serval for the foreseeable future.
Contributor guide
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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
Start by reading the abridgment-alignment requirements in this issue and the referenced yasa and Champollion papers. The payload names no files, tests, implementation entry point, or acceptance criteria; the stated boundary is that substantially abridged non-Scripture text is out of scope for Serval for the foreseeable future.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100