SpaCy
spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.
Unlike NLTK, which is widely used for teaching and research, spaCy focuses on providing software for production usage. As of version 1.0, spaCy also supports deep learning workflows that allow connecting statistical models trained by popular machine learning libraries like TensorFlow, PyTorch or MXNet through its own machine learning library Thinc. Using Thinc as its backend, spaCy features convolutional neural network models for part-of-speech tagging, dependency parsing, text categorization and named entity recognition. Prebuilt statistical neural network models to perform these task are available for English, German, Greek, Spanish, Portuguese, French, Italian, Dutch, Lithuanian and Norwegian, and there is also a multi-language NER model. Additional support for tokenization for more than 50 languages allows users to train custom models on their own datasets as well.Main features
spaCy comes with several extensions and visualizations that are available as free, open-source libraries:
- Thinc: A machine learning library optimized for CPU usage and deep learning with text input.
- sense2vec: A library for computing word similarities, based on Word2vec and sense2vec.
- displaCy: An open-source dependency parse tree visualizer built with JavaScript, CSS and SVG.
- displaCyENT: An open-source named entity visualizer built with JavaScript and CSS.
