While it's possible that some parts of NLTK may be unpythonic, I disagree that it's somehow inaccessible or hard to use. The NLTK project is fairly well-documented, and I've never had any difficulty using it. Also, all the NLTK code I've ever examined looks Pythonic to me, unlike the Java-style Python that I sometimes see coming out of academia; they follow PEP8 and have a developer style guide. There may be pockets of unpythonic code, but I've not come across any.
NLTK is also free and open-source, with a liberal license (Apache), which I appreciate greatly.
Also, I don't understand what you mean by nltk being a library for building NLP solutions, rather than NLP-powered apps. Can you expand on that?
Re: NER, I found this gist (not my own) for a basic example of entity extraction with nltk: https://gist.github.com/322906/90dea659c04570757cccf0ce1e6d2... This looks pretty straight-forward to me. What NLP toolkit are you using for the NER service your Chrome extension calls, if not NLTK?
It isn't just extraction, but the entire process, from training a dictionary, to training it, etc. Have you tried training your own dictionary to extract custom entities? It is "non-trivial".
NLTK is also free and open-source, with a liberal license (Apache), which I appreciate greatly.
Also, I don't understand what you mean by nltk being a library for building NLP solutions, rather than NLP-powered apps. Can you expand on that?
Re: NER, I found this gist (not my own) for a basic example of entity extraction with nltk: https://gist.github.com/322906/90dea659c04570757cccf0ce1e6d2... This looks pretty straight-forward to me. What NLP toolkit are you using for the NER service your Chrome extension calls, if not NLTK?