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Evaluation for morphologically rich language: Russian NLP
P. 300–306.
Abstract - RU-EVAL is a biennial event organized in order to estimate the state of the art in Russian NLP resources, methods and toolkits and to compare various methods and principles implemented for Russian. Russian could be treated as an under-resourced language due to the lack of free distributable gold standard corpora for different NLP tasks (each team tried to work out their own standards). Thus, our goal was to work out the uniform basis for comparison of systems based on different theoretical and engineering approaches, to build evaluation resources, to provide a flexible system of evaluation in order to differentiate between non-acceptable and linguistically “admissible” errors. The paper reports on three events devoted to morphological tagging, dependency parsing and anaphora resolution, respectively.
In book
Vol. 1. , Las Vegas: CSREA Press, 2015.
Glazkova A., Lyashevskaya O., Morozov D. et al., Journal of Mathematical Sciences 2025 Vol. 546 P. 32–47
This paper addresses the task of lemmatizing abbreviations in the Russian language. Abbreviation lemmatization is particularly challenging, as it involves not only transforming a word into its normal form but also correctly expanding the abbreviation. We explore two approaches to this task, both leveraging large pretrained language models. The first approach is generative, where the ...
Added: March 10, 2026
Tartu: University of Tartu Library, 2025.
The third workshop on resources and representations for under-resourced languages and domains was held in Tallinn, Estonia, on March 2nd, 2025. The workshop was conducted in person but also provided an option for online participation. In alignment with the goals of the previous two workshops in 2020 and 2023, RESOURCEFUL-2025 explored the role of resource ...
Added: July 17, 2025
Afanasev I., Lyashevskaya O., , in: Proceedings of the 2023 CLASP Conference on Learning with Small Data (LSD).: Gothenburg: Association for Computational Linguistics, 2023. P. 167–175.
The growing need for using small data distinguished by a set of distributional properties becomes all the more apparent in the era of large language models (LLM). In this paper, we show that for the lemmatisation of the web as corpora texts, heterogeneous social media texts, and dialect texts, the morphological tagging by a model ...
Added: December 10, 2023
Lyashevskaya O., Afanasev I., Stefan Rebrikov et al., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог». Вып. 22.Вып. 22.: [б.и.], 2023. P. 307–318.
An updated annotation of the Main, Media, and some other corpora of the Russian National Corpus (RNC) features the part-of-speech and other morphological information, lemmas, dependency structures, and constituency types. Transformer-based architectures are used to resolve the homonymy in context according to a schema based on the manually disambiguated subcorpus of the Main corpus (morphology ...
Added: September 15, 2023
The Use of Khislavichi Lect Morphological Tagging to Determine its Position in the East Slavic Group
Afanasev I., , in: Proceedings of Tenth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2023).: Association for Computational Linguistics, 2023. P. 174–186.
The study of low-resourced East Slavic lects is becoming increasingly relevant as they face the prospect of extinction under the pressure of standard Russian while being treated by academia as an inferior part of this lect. The Khislavichi lect, spoken in a settlement on the border of Russia and Belarus, is a perfect example of ...
Added: May 15, 2023
Association for Computational Linguistics, 2023.
These proceedings include the 23 papers presented at the 10th Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial), co-located with the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL). Both EACL and VarDial were held in Dubrovnik, Croatia, in a hybrid format, allowing participants to attend on-site or ...
Added: May 15, 2023
Association for Computational Linguistics, 2020.
Added: November 18, 2020
Shavrina T., Emelyanov A., Fenogenova A. et al., , in: Proceedings of The 12th Language Resources and Evaluation ConferenceVol. 12.: European Language Resources Association (ELRA), 2020. P. 2276–2284.
Artificial General Intelligence (AGI) is showing growing performance in numerous applications - beating human performance in Chess and Go, using knowledge bases and text sources to answer questions (SQuAD) and even pass human examination (Aristo project). In this paper, we describe the results of AI Journey, a competition of AI-systems aimed to improve AI performance ...
Added: June 15, 2020
European Language Resources Association (ELRA), 2020.
Welcome to the 12th edition of LREC . . . that should have been in Marseille, first time in France! Unfortunately not now, in May 2020. Now my welcome is completely virtual, to all of you authors of these Proceedings papers and to the colleagues who will look at these. Virtual but not less sincere. ...
Added: June 15, 2020
Starchenko A., Lyashevskaya O., , in: Digital Transformation and Global Society. Fourth International Conference, DTGS 2019, St. Petersburg, Russia, June 19–21, 2019, Revised Selected Papers.: Springer, 2019. P. 732–743.
The poetic texts pose a challenge to full morphological tagging and lemmatization since the authors seek to extend the vocabulary, employ morphologically and semantically deficient forms, go beyond standard syntactic templates, use non-projective constructions and non-standard word order, among other techniques of the creative language game. In this paper we evaluate a number of probabilistic ...
Added: June 12, 2019
Starchenko A., Kazakevich L., Lyashevskaya O., / NRU HSE. Series WP BRP "Linguistics". 2018. No. 76.
The poetic texts pose a challenge to full morphological tagging and lemmatization since the authors seek to extend the vocabulary, employ morphologically and semantically deficient forms, go beyond standard syntactic templates, use non-projective constructions and non-standard word order, among other techniques of the creative language game. In this paper we evaluate a number of probabilistic ...
Added: December 12, 2018
Дроганова К. А., Lyashevskaya O., Zeman D., , in: Proceedings of TLT 2018 International Workshop on Treebanks and Linguistic Theories, 13-14 November 2018, Oslo, Norway. NEALT Proceedings Series.: Linköping University Electronic Press, 2018. P. 52–65.
In this paper we focus on syntactic annotation consistency within Universal Dependencies (UD) treebanks for Russian: UD_Russian-SynTagRus, UD_Russian-GSD, UD\_Russian-Taiga, and UD_Russian-PUD. We describe the four treebanks, their distinctive features and development. In order to test and improve consistency within the treebanks, we reconsidered the experiments by Martinez Alonso and Zeman; our parsing experiments were conducted ...
Added: November 6, 2018
Fenogenova A., Kazorin V., Karpov I. et al., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 11–17.
Automatic morphological analysis is one of the fundamental and significant tasks of NLP (Natural Language Processing). Due to special features of Internet texts, as they can be both normative texts (news, fiction, nonfiction) and less formal texts (such as blogs and texts from social networks), the morphological tagging has become non-trivial and an actual task. ...
Added: October 5, 2018
Azerkovich I., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 107–112.
Semantic information has been deemed a valuable resource for
solving the task of coreference resolution by many researchers. Unfortunately,
not much has been done in the direction of using this data when working with
Russian data. This work describes the first step of a research, attempting to create
a coreference resolution system for Russian based on semantic data, concerned
with ...
Added: September 5, 2018
Toldova S., Ionov M., , in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2016Vol. 1. Issue 9623.: Springer Publishing Company, 2018. P. 648–662.
This paper concerns discourse-new mention detection in Russian. This might be helpful for different NLP applications such as coreference resolution, protagonist identification, summarization and different tasks of information extraction to detect the mention of an entity newly introduced into discourse. In our work, we are dealing with the Russian where there is no grammatical devices, ...
Added: September 1, 2018
Lyashevskaya O., Bocharov V., Sorokin A. et al., Jazykovedny Casopis 2017 Vol. 68 No. 2 P. 258–267
The paper describes the preparation and development of the text collections within the framework of MorphoRuEval-2017 shared task, an evaluation campaign designed to stimulate development of the automatic morphological processing technologies for Russian. The main challenge for the organizers was to standardize all available Russian corpora with the manually verified high-quality tagging to a single ...
Added: January 30, 2018
Toldova S., Max Ionov, , in: CLLS 2016. Computational Linguistics and Language Science. Proceedings of the Workshop on Computational Linguistics and Language Science. Moscow, Russia, April 26, 2016Vol. 1886.: Aachen: CEUR Workshop Proceedings, 2017. Ch. 5 P. 33–41.
This paper describes a pilot study of the problem of detecting singleton mentions in Russian texts. A noun phrase is considered a singleton mention if it is the only referent of some entity. We discuss various morphosyntactic and lexical features, some of which were used for analogous tasks for English and propose new features derived ...
Added: November 9, 2017
Toldova S., Maxim Ionov, , in: Computational Linguistics and Intellectual Technologies. International Conference "Dialogue 2017" ProceedingsVol. 1. Issue 16 (23).: M.: -, 2017. P. 339–348.
This paper presents the results of our experiments on building a general coreference resolution system for Russian. The main aim of those experiments was to set a baseline for this task for Russian using the standard set of features developed and tested for coreference resolution systems created for other languages. We propose several baseline systems, ...
Added: July 12, 2017
Mention Detection for Improving Coreference Resolution in Russian Texts: A Machine Learning Approach
Toldova S., Ionov M., Computacion y Sistemas 2016 Vol. 20 No. 4 P. 681–696
The paper concerns discourse-new referent detection. The task of coreference resolution is essential in many text-mining applications. The focus in this task is to detect noun phrases (NPs) that refer to the same entity. In languages without articles, there are no overt grammatical clues in an NP for whether it introduces a new referent into ...
Added: December 27, 2016