spaCy is a free open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more.
spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. It's designed specifically for production use and helps you build applications that process and understand large volumes of text. It can be used to build information extraction or natural language understanding systems, or to pre-process text for deep learning.
4500 / day
5000 / day
2.8 pages per visit
Domain Rating
Domain Authority
Citation Level
English, etc
Segmenting text into words, punctuations marks etc.
Assigning word types to tokens, like verb or noun.
Assigning syntactic dependency labels, describing the relations between individual tokens, like subject or object.
Labelling named real-world objects, like persons, companies or locations.
Disambiguating textual entities to unique identifiers in a knowledge base.
Comparing words, text spans and documents and how similar they are to each other.
Assigning categories or labels to a whole document, or parts of a document.
Finding sequences of tokens based on their texts and linguistic annotations, similar to regular expressions.
Updating and improving the statistical models' predictions.
Saving objects to files or byte strings.
MIT
https://github.com/explosion/spaCy
https://spacy.io/usage
spaCy has a large and active community. You can join the discussion on GitHub, Gitter, or Stack Overflow.
Explosion AI offers commercial support, consulting, and custom development for spaCy.
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