MaartenGr / MaartenGr/BERTopic
Semantic Sentence Tokenization
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- Dominant language
- Python
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Description
I'm working with a corpus that primarily consists of longer documents. I'm seeking recommendations for the most effective approach to semantically tokenize them.
Examples:
```
Original Text: "I like the ambiance but the food was terrible."
Desired Output: ["I like the ambiance"] ["but the food was terrible."]
Original Text: "I don't know. I like the restaurant but not the food."
Desired Output: ["I don't know."] ["I like the restaurant"] ["but not the food."]
```
Any suggestions or advice on how to achieve this would be greatly appreciated!
Contributor guide
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
The issue does not name a source file, entry point, or test. First determine whether semantic sentence tokenization is intended as a BERTopic feature or only usage guidance, then inspect the relevant text-processing and document-ingestion paths. Done should include an agreed behavior for the examples and a test or documentation update that verifies it.
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
- 20/100