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I don't understand the hype around spacy especially when it relies on (closed source) annotated corpus to do all of its job. The default models fail in simple cases. And it takes a lot to train a new model on new corpus.

I am wondering how people solve actual problems with spacy. What are the use cases? Is Spacy used in question answering sytems or summarization pipelines? Maybe conceptual search?

I prefer the approach of link grammar / relex which are based on dictionaries / grammars, it seems easier and less error prone.

Prodigy is genius! More tools like that will be built in the next few years...



> I prefer the approach of link grammar / relex which are based on dictionaries / grammars, it seems easier and less error prone.

Can you link to something open source that outperforms spacy on the basic NLP tasks (NER, POS, dependency parsing)?


all at the same time, I agree that there is no equivalent; that said, for each tasks there is better tools.




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