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python libraries: foliapy split off from pynlpl, added foliapy and revised pynlpl
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README.md

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@@ -160,7 +160,8 @@ Material can be found [here](https://github.com/aws-samples/aws-machine-learning
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- [AllenNLP](https://github.com/allenai/allennlp) - An NLP research library, built on PyTorch, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.
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- [PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP) - NLP research toolkit designed to support rapid prototyping with better data loaders, word vector loaders, neural network layer representations, common NLP metrics such as BLEU
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- [Rosetta](https://github.com/columbia-applied-data-science/rosetta) - Text processing tools and wrappers (e.g. Vowpal Wabbit)
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- [PyNLPl](https://github.com/proycon/pynlpl) - Python Natural Language Processing Library. General purpose NLP library for Python. Also contains some specific modules for parsing common NLP formats, most notably for [FoLiA](https://proycon.github.io/folia/), but also ARPA language models, Moses phrasetables, GIZA++ alignments.
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- [PyNLPl](https://github.com/proycon/pynlpl) - Python Natural Language Processing Library. General purpose NLP library for Python, handles some specific formats like ARPA language models, Moses phrasetables, GIZA++ alignments.
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- [foliapy](https://github.com/proycon/foliapy) - Python library for working with [FoLiA](https://proycon.github.io/folia/), an XML format for linguistic annotation.
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- [PySS3](https://github.com/sergioburdisso/pyss3) - Python package that implements a novel white-box machine learning model for text classification, called SS3. Since SS3 has the ability to visually explain its rationale, this package also comes with easy-to-use interactive visualizations tools ([online demos](http://tworld.io/ss3/)).
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- [jPTDP](https://github.com/datquocnguyen/jPTDP) - A toolkit for joint part-of-speech (POS) tagging and dependency parsing. jPTDP provides pre-trained models for 40+ languages.
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- [BigARTM](https://github.com/bigartm/bigartm) - a fast library for topic modelling

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