🚀 100 Times Faster Natural Language Processing in Python
When we published our Python coreference resolution package✨ last year, we got an amazing feedback from the community and people started to use it for many applications 📚, some very different from our original dialog use-case 👥.
And we discovered that, while the speed was totally fine for dialog messages, it could be really slow 🐌 on larger news articles.
I decided to investigate this in details and the result is NeuralCoref v3.0 which is about 100 times faster 🚀 than the previous version (several thousands words per seconds) while retaining the same accuracy, and the easiness of use and eco-system of a Python library.
So I am a bit cheating here because we will be talking about Python, but also about some Cython magic — but, you know what? Cython is a superset of Python, so don’t let that scares you away!
One last thing before we start: I also published a Jupyter Notebook with the working examples I talk about in this post. Try it out!
