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Hi @HaveF, thanks for stopping by!
I don't have benchmarks at hand, so while it's more or less a fact that lemmatization can help in several NLP tasks, I am not sure how much better an LLM works when the prompt is lemmatized.
In the context of prompt engineering, it's more the other way around: I use lemmatization to shrink the prompt and pay less money since I have less tokens, then the challenge is to verify the query is still effective. In my quite limited experiments I couldn't find a use case where a lemmatized prompt was giving back obviously wrong results, but your mileage might vary.
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thanks for your words!
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