Introduction to StanfordNLP: An Incredible State-of-the-Art NLP Library for 53 Languages (with Python code)
Introduction
A common challenge I came across while learning Natural Language Processing (NLP) – can we build models for non-English languages? The answer has been no for quite a long time. Each language has its own grammatical patterns and linguistic nuances. And there just aren’t many datasets available in other languages.
That’s where Stanford’s latest NLP library steps in – StanfordNLP.
I could barely contain my excitement when I read the news last week. The authors claimed StanfordNLP could support more than 53 human languages! Yes, I had to double-check that number.
I decided to check it out myself. There’s no official tutorial for the library yet so I got the chance to experiment and play around with it. And I found that it opens up a world of endless possibilities. StanfordNLP contains pre-trained models for rare Asian languages like Hindi, Chinese and Japanese in their original scripts.
The ability to work