We are happy to announce we have released the first stable version of NLP-Cube.
NLP-Cube is a Python package that provides state-of-the-art text segmentation (tokenization and sentence-splitting), lemmatization, POS tagging and dependency parsing for over 50 languages.
The project's repository is https://github.com/adobe/NLP-Cube Instalation is simple: 'pip install nlpcube', and usage is as simple as 'sentences = cube("your text here")'. Here's a 1-minute usage example: https://github.com/adobe/NLP-Cube/blob/master/examples/simple_example.ipynb
We have released models for: Afrikaans, Ancient-Greek, Arabic, Armenian, Basque, Bulgarian, Buryat, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German , Gothic, Greek , Hebrew, Hindi, Hungarian, Indonesian, Irish, Italian, Japanese, Kazakh, Korean, Kurmanji, Latin, Latvian, North_Sami, Norwegian-Bokmaal, Norwegian-Nynorsk, Old_Church_Slavonic, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swedish, Turkish, Ukrainian, Urdu, Uyghur and Vietnamese. All these are based on the Universal Dependencies Treebanks.
We'll add more help, more examples and advanced usage in the days to come. A NER (named entity recognizer) is also available and we'll release pre-trained models soon. Finally, we're very happy to hear your thoughts/requests/feedback.
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