StanfordNLP

StanfordNLP is the combination of the software package used by the Stanford team in the CoNLL 2018 Shared Task on Universal Dependency Parsing, and the group's official Python interface to the Stanford CoreNLP software. Aside from the functions it inherits from CoreNLP, it contains tools to convert a string of text to lists of sentences and words, generate base forms of those words, their parts of speech and morphological features, and a syntactic structure that is designed to be parallel among more than 70 languages. This package is built with highly accurate neural network components that enables efficient training and evaluation with your own annotated data. The modules are built on top of PyTorch. To see StanfordNLP's neural pipeline in action, you can launch the Python interactive interpreter, and try the following commands At the end, you should be able to see the dependency parse of the first sentence in the example.