tokenization issues for non-ascii texts

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
25/100
Issue type
Bug
Clarity
Needs clarification
Activity status
Stale
Tech stack
python
Domain
backend

Research direction

Start by locating the NLTK tokenizer invocation and reproducing the issue with fancy quotation marks in non-ASCII text. Compare tokenization of quotation marks and other symbols, then consider the behavior complete when punctuation is separated from words without breaking existing parsing.

Written by the indexing model from the issue text.

Description

The NLTK tokenizer used in the code doesn't handle fancy quotation marks very well. They just end up attached to words rather than being separate tokens.

We should probably either preprocess the input that is passed to the tokenizer, find another tokenizer, or fix the current one.

There may be some issues related to other types of symbols as well.

Dominant language
Python
Stars
128
Forks
24
No merged PRs in 30d

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