heatherleaf / heatherleaf/korpsearch

n-gram character index

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Dominant language
Python
Stars
2
Forks
6
PR merge metrics
No merged PRs in 30d

Description

Currently the indexes are on token level:

  • singleton index: [lemma] or [pos]
  • pairwise index: [pos][lemma] or [pos][][pos]
  • etc

Inspired by plocate, we could create character indexes instead (3-grams or 4-grams or ...). Where the characters are for lemmas, pos, etc, or combinations.

Instead of the entries [lemma="car"], [lemma="card"], [lemma="cart"], and [lemma="ward"] we would get:

  • [lemma="*car*"], [lemma="*ard*"], [lemma="*art*"], and [lemma="*war*"]

This would only be interesting for some features (lemma, word, etc)

For combined features: [pos="ADJ"][lemma="*car*"], [pos="DET"][lemma="*art*"], [lemma="*war*"][pos="NN"], etc.

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the existing token-level index implementation and how queries for lemma, word, POS, and combined features are handled. Define which features and n-gram sizes are supported, then verify that the example character-index queries produce correct search results.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
search
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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