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Universal Dependencies treebank based on data samples extracted from Taiga Corpus and MorphoRuEval-2017 text collections.


UD Russian Taiga has been developed at the School of Linguistics, National Research University Higher School of Economics in Moscow (HSE/Vyshka). The selection of texts is meant to represent those registers that have not been covered by UD Russian SynTagRus and UD Russian Google Stanford Dependencies, mainly e-communication (blogs and social media). The sentences are extracted from two open data collections. Taiga Corpus ( is an open-source corpus for machine learning collected by students as part of the curriculum of the MA Program in Computational Linguistics at HSE. MorphoRuEval 2017 text collections ( is an output of the RuEval shared task 'Evaluation of Russian NLP: Morphological analysis,

The plain text data were tokenized, lemmatized and parsed using UDpipe ( and checked manually. Corrections were made at all levels: tokenization, lemmata, pos, features, dependency relations.


  • blogs and social media: 87% main source:

  • naïve poetry: 11%  main source:

  • news: 1% The tiny news collection was used to train annotators and check annotation consistency with other UD treeabnks.

Data split


  • training: 50% (10K tokens, 880 sentences)

  • test: 50% (10K tokens, 884 sentences)


We are grateful to all the contributors to the original open Russian data collections and especially to Tatiana Shavrina (Taiga) and Alena Fenogenova (MorphoRuEval-2017 data set).


  • Lyashevskaya, Olga, Kira Droganova, Daniel Zeman, Maria Alexeeva, Tatiana Gavrilova, Nina Mustafina, and Elena Shakurova. (2016). Universal Dependencies for Russian: a New Syntactic Dependencies Tagset. In: Series: Linguistics, WP BRP 44/LNG/2016. Moscow.

  • Sorokin, Andrey, Tatiana Shavrina, Olga Lyashevskaya, Victor Bocharov, Svetlana Alexeeva, Kira Droganova, Alena Fenogenova, and Dmitry Granovsky. (2017). MorphoRuEval-2017: an Evaluation Track for the Automatic Morphological Analysis Methods for Russian. In Computational Linguistics and Intellectual Technologies, Proceedings of Dialog 2017, Moscow. No 16 (23). Vol. 1, 297-313.

  • Lyashevskaya, Olga, Victor Bocharov, Alexey Sorokin, Tatiana Shavrina, Dmitry Granovsky, and Svetlana Alexeeva. (2017). Text collections for evaluation of Russian morphological taggers. Jazykovedny Casopis, 68 (2), 2017: 258-267.

  • Shavrina, Tatiana, Olga Shapovalova. (2017) To the methodology of corpus construction for machine learning: «Taiga» syntax tree corpus and parser. In Proceedings of the International Conference "CORPORA 2017", Saint-Petersbourg, Russia.


  • 2018-07-01 v2.2
    • First official release.
=== Machine-readable metadata (DO NOT REMOVE!) ================================
Data available since: UD v2.2
License: CC BY-SA 4.0
Includes text: yes
Genre: blog news poetry social
Lemmas: manual native
UPOS: manual native
XPOS: manual native
Features: manual native
Relations: manual native
Contributors: Lyashevskaya, Olga; Rudina, Olga
Contributing: elsewhere
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