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We present an update to UDPipe 1.0 (Straka et al., 2016), a trainable pipeline which performs sentence segmentation, tokenization, POS tagging, lemmatization and dependency parsing. We provide models for all 50 languages of UD 2.0, and furthermore, the pipeline can be trained easily using data in CoNLL-U format. For the purpose of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, the updated UDPipe 1.1 was used as one of the baseline systems, finishing as the 13th system of 33 participants. A further improved UDPipe 1.2 participated in the shared task, placing as the 8th best system, while achieving low running times and moder- ately sized models. The tool is available under open-source Mozilla Public Licence (MPL) and provides bindings for C++, Python (through ufal.udpipe PyPI package), Perl (through UFAL::UDPipe CPAN package), Java and C#.

Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe