stanfordnlp v0.1.0 Release Notes
Release Date: 2019-01-30 // about 5 years ago-
🚀 The initial release of 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. 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 (v1.0.0).
StanfordNLP features:
- Native Python implementation requiring minimal efforts to set up;
- 📈 Full neural network pipeline for robust text analytics, including tokenization, multi-word token (MWT) expansion, lemmatization, part-of-speech (POS) and morphological features tagging and dependency parsing;
- 👍 Pretrained neural models supporting 53 (human) languages featured in 73 treebanks;
- A stable, officially maintained Python interface to CoreNLP.