spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. spaCy comes with pretrained statistical models and word vectors, and currently supports tokenization for 50+ languages. It features state-of-the-art speed, convolutional neural network models for tagging, parsing and named entity recognition and easy deep learning integration. It's commercial open-source software, released under the MIT license.

 

Features

  • Non-destructive tokenization
  • Named entity recognition
  • Support for 55+ languages
  • 17 statistical models for 11 languages
  • pretrained word vectors
  • State-of-the-art speed
  • Easy deep learning integration
  • Part-of-speech tagging
  • Labelled dependency parsing
  • Syntax-driven sentence segmentation
  • Built in visualizers for syntax and NER
  • Convenient string-to-hash mapping
  • Export to numpy data arrays
  • Efficient binary serialization
  • Easy model packaging and deployment
  • Robust, rigorously evaluated accuracy


Get Started with the service

: Free of charge

Support

Helpdesk: contact@explosion.ai

Documentation: Documentation

Access the service

Request - Source Code : https://github.com/explosion/spaCy

Terms of Use: MIT

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