Stanza

From Source

Alternatively, you can also install from source of this git repository, which will give you more flexibility in developing on top of Stanza. For this option, run

git clone https://github.com/stanfordnlp/stanza.git
cd stanza
pip install -e .

Running Stanza

Accessing Java Stanford CoreNLP software

Aside from the neural pipeline, this package also includes an official wrapper for accessing the Java Stanford CoreNLP software with Python code.

There are a few initial setup steps.

Download Stanford CoreNLP and models for the language you wish to use
Put the model jars in the distribution folder
Tell the Python code where Stanford CoreNLP is located by setting the CORENLP_HOME environment variable (e.g., in *nix): export CORENLP_HOME=/path/to/stanford-corenlp-4.5.3

We provide comprehensive examples in our documentation that show how one can use CoreNLP through Stanza and extract various annotations from it.

Online Colab Notebooks

To get your started, we also provide interactive Jupyter notebooks in the demo folder. You can also open these notebooks and run them interactively on Google Colab. To view all available notebooks, follow these steps:

Go to the Google Colab website
Navigate to File -> Open notebook, and choose GitHub in the pop-up menu
Note that you do not need to give Colab access permission to your GitHub account
Type stanfordnlp/stanza in the search bar, and click enter

Trained Models for the Neural Pipeline

We currently provide models for all of the Universal Dependencies treebanks v2.8, as well as NER models for a few widely-spoken languages. You can find instructions for downloading and using these models here.

Batching To Maximize Pipeline Speed