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The theoretically "best" algorithm may not necessarily be the one that fits a particular task or set of constraints the best. It is presumptuous of the author to know what's best for every user of the toolkit.

I suggest that the author, being so wise in the ways of NLP science, channel this outrage and write "NLTK: The Good Parts" to save the rest of the world from stumbling blindly in the dark wilderness of ignorance.



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