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It is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. | It is an open-source no-code system for text annotation and building text classifiers. With this, domain experts can quickly create custom Natural Language Processing (NLP) models by themselves, with no dependency on NLP experts. No AI knowledge needed; from task definition to working model in just a few hours! |
Native Python implementation requiring minimal efforts to set up;
Full neural network pipeline for robust text analytics, including tokenization, multi-word token (MWT) expansion, lemmatization, part-of-speech (POS) and morphological features tagging, dependency parsing, and named entity recognition;
Pretrained neural models supporting 66 (human) languages;
A stable, officially maintained Python interface to CoreNLP | Extensible architecture;
Open source;
No AI knowledge needed;
From task definition to working model in just a few hours |
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GitHub Stars 7.6K | GitHub Stars 269 |
GitHub Forks 926 | GitHub Forks 41 |
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Followers 34 | Followers 3 |
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