If anyone is interested in NLP and hasn't had the chance to use spaCy yet, give it a go now - it's just two commands: "pip install spacy" and "python -m spacy.en.download" =]
spaCy is perfect for web-scale NLP (a term I don't use lightly consider I crawl billions of pages a month) and is AGPLv3 for hobbyists / academics / open source developers. It comes with an existing language model for English, a concise API, and many other goodies baked in by default (i.e. word vector representations). Even though it's in Python and near state of the art in terms of accuracy, it's far faster than just about any other parser out there. Finally, the demos and documentation are consistently strong and continuously improving.
I'd highly recommend checking out the "marking adverbs" tutorial, which shows how to develop features you might use in a proofreading tool in a few dozen lines of Python.
n.b. I was in the same NLP research group with Matthew Honnibal whilst he was obtaining his PhD at the University of Sydney, so I'm biased, but only as I've seen his work in person!
spaCy is perfect for web-scale NLP (a term I don't use lightly consider I crawl billions of pages a month) and is AGPLv3 for hobbyists / academics / open source developers. It comes with an existing language model for English, a concise API, and many other goodies baked in by default (i.e. word vector representations). Even though it's in Python and near state of the art in terms of accuracy, it's far faster than just about any other parser out there. Finally, the demos and documentation are consistently strong and continuously improving.
I'd highly recommend checking out the "marking adverbs" tutorial, which shows how to develop features you might use in a proofreading tool in a few dozen lines of Python.
http://spacy.io/tutorials/mark-adverbs/
n.b. I was in the same NLP research group with Matthew Honnibal whilst he was obtaining his PhD at the University of Sydney, so I'm biased, but only as I've seen his work in person!