README

UDPipe
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UDPipe is a trainable pipeline for tokenization, tagging, lemmatization and
dependency parsing of CoNLL-U files. UDPipe is language-agnostic and can be
trained given annotated data in CoNLL-U format
(http://universaldependencies.org/format.html). Trained models are provided for
nearly all UD treebanks (http://universaldependencies.org). UDPipe is available
as a binary for Linux/Windows/OS X, as a library for C++, Python, Perl, Java,
C#, and as a web service. Third-party R CRAN package
(https://CRAN.R-project.org/package=udpipe) also exists.

UDPipe is a free software distributed under the Mozilla Public License 2.0
(http://www.mozilla.org/MPL/2.0/) and the linguistic models are free for
non-commercial use and distributed under the CC BY-NC-SA
(http://creativecommons.org/licenses/by-nc-sa/4.0/) license, although for some
models the original data used to create the model may impose additional
licensing conditions. UDPipe is versioned using Semantic Versioning
(http://semver.org/).

Copyright 2017 by Institute of Formal and Applied Linguistics, Faculty of
Mathematics and Physics, Charles University, Czech Republic.

UDPipe website http://ufal.mff.cuni.cz/udpipe contains download links of both
the released packages and trained models, hosts documentation and offers online
web service.

UDPipe development repository http://github.com/ufal/udpipe is hosted on GitHub.

Third-party contribution: Instructions how to build UDPipe REST server as Docker
image is here: http://github.com/samisalkosuo/udpipe-rest-server-docker.
Instructions how to train UDPipe language models using a Docker image is also
there.