EstNLTK neural -- EstNLTK's linguistic analysis based on neural models

This package contains EstNLTK's linguistic analysis tools that use neural models:

• neural morphological tagger ( disambiguator );
• bert embeddings tagger;
• bert NER tagger;
• stanza syntax tagger and stanza ensemble syntax tagger;
• pronominal coreference tagger v1 (relies on stanza for input preprocessing);

Note: these tools require installation of deep learning frameworks (tensorflow, pytorch), and are demanding for computational resources; they also rely on large models which need to be downloaded separately.

The EstNLTK project is funded by EKT (Eesti Keeletehnoloogia Riiklik Programm).

Installation

EstNLTK-neural is available as a PyPI wheel:

pip install estnltk_neural

And as an Anaconda package:

conda install -c estnltk -c conda-forge estnltk_neural

Supported Python versions: 3.8+

Neural models

Models required by neural tools are large, and therefore cannot be distributed with this package. However, our tagger classes are implemented in a way that once you create an instance of a neural tagger, you'll be asked for a permission to download missing models, and if you give the permission, the model will be downloaded (and installed in a proper location) automatically. If needed, you can also change the default location where downloaded models will be placed, see this tutorial for details.

Documentation

EstNLTK's NLP component tutorials also cover information about neural taggers.

Source

The source of the last release is available at the main branch.

License: GNU General Public License v2.0

(C) University of Tartu