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A morphological processor for Russian with extended functionality
P. 22–33.
Bolshakova E. I., Sapin A.
The paper presents an open-source morphological processor of Russian texts recently developed and named CrossMorphy. The processor performs lemmatization, morphological tagging of both dictionary and non-dictionary words, contextual and non-contextual morphological disambiguation, generation of word forms, as well as morphemic parsing of words. Besides the extended functionality, emphasis is put on linguistic quality of word processing and easy integration into programming projects. CrossMorphy is fully implemented in C++ programming language on the base of OpenCorpora vocabulary data.
In book
Vol. 10716. , Cham: Springer, 2018.
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
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
Sorokin A., Shavrina T., Lyashevskaya O. et al., , in: Computational Linguistics and Intellectual Technologies. International Conference "Dialogue 2017" ProceedingsVol. 1. Issue 16 (23).: M.: -, 2017. P. 297–313.
MorphoRuEval-2017 is an evaluation campaign designed to stimulate the development of the automatic morphological processing technologies for Russian, both for normative texts (news, fiction, nonfiction) and those of less formal nature (blogs and other social media). This article compares the methods participants used to solve the task of morphological analysis. It also discusses the problem ...
Added: October 9, 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
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., Lyashevskaya O., Bonch-Osmolovskaya A. A. et al., , in: Proceedings on the International Conference on Artificial Intelligence (ICAI)Vol. 1.: Las Vegas: CSREA Press, 2015. 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 ...
Added: December 9, 2015
Klyshinskiy E., Рысаков С. В., Новые информационные технологии в автоматизированных системах 2015 С. 555–563
Статья знакомит читателя со статистическими методами устранения морфологической неоднозначности. Описывается процесс насыщения, параметры методов и n-грамм. Большое внимание уделено методам снятия омонимии, в обзоре которых описания сопровождены практическими оценками и даны алгоритмы их работы. В конце приведено сравнение качества методов дизамбигуации, осуществлённое авторами. ...
Added: November 25, 2015
Kuzmenko E., Mustakimova E., , in: Компьютерная лингвистика и интеллектуальные технологии. По материалам ежегодной Международной конференции "Диалог" (2015).: М.: Изд-во РГГУ, 2015. P. 388–398.
The problem of morphological ambiguity is widely addressed in the modern NLP. Mostly ambiguity is resolved with the use of large manually-annotated corpora and machine learning. However, such methods are not always available, as good training data is not accessible for all languages. In this paper we present a method of disambiguation without gold standard ...
Added: July 30, 2015