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UD Russian Taiga

Language: Russian (code: ru)
Family: Indo-European, Slavic

This treebank has been part of Universal Dependencies since the UD v2.2 release.

The following people have contributed to making this treebank part of UD: Olga Lyashevskaya, Olga Rudina.

Repository: UD_Russian-Taiga
Search this treebank on-line: PML-TQ
Download all treebanks: UD 2.2

License: CC BY-SA 4.0

Genre: blog, news, poetry, social

Questions, comments? General annotation questions (either Russian-specific or cross-linguistic) can be raised in the main UD issue tracker. You can report bugs in this treebank in the treebank-specific issue tracker on Github. If you want to collaborate, please contact [olesar (æt) yandex • ru]. Development of the treebank happens outside the UD repository. If there are bugs, either the original data source or the conversion procedure must be fixed. Do not submit pull requests against the UD repository.

Annotation Source
Lemmas annotated manually, natively in UD style
UPOS annotated manually, natively in UD style
XPOS annotated manually
Features annotated manually, natively in UD style
Relations annotated manually, natively in UD style


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 (https://tatianashavrina.github.io/taiga_site/) 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 (https://github.com/dialogue-evaluation/morphoRuEval-2017) is an output of the RuEval shared task ‘Evaluation of Russian NLP: Morphological analysis, http://www.dialog-21.ru/en/evaluation/2017/morphology/).

The plain text data were tokenized, lemmatized and parsed using UDpipe (http://ufal.mff.cuni.cz/udpipe) and checked manually. Corrections were made at all levels: tokenization, lemmata, pos, features, dependency relations.


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).


Statistics of UD Russian Taiga

POS Tags






Tokenization and Word Segmentation



Nominal Features

Degree and Polarity

Verbal Features

Pronouns, Determiners, Quantifiers

Other Features


Auxiliary Verbs and Copula

Core Arguments, Oblique Arguments and Adjuncts

Here we consider only relations between verbs (parent) and nouns or pronouns (child).

Relations Overview