Olga Lyashevskaya

National Research University Higher School of Economics

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Kira Droganova

Charles University

Francis M. Tyers

Indiana University

Daniel Zeman

Charles University

Normunds Grūzītis

University of Latvia

Marco Passarotti

Università Cattolica del Sacro Cuore

Cristina Bosco

University of Turin

Simon Krek

University of Ljubljana

Tomaž Erjavec

Jožef Stefan Institute

Verginica Barbu Mititelu

Romanian Academy

Nikola Ljubešić

Jožef Stefan Institute

Cooperative Institutions

National Research University Higher School of Economics

Charles University

Centre National de la Recherche Scientifique

University of Helsinki

Google (United States)

Universidade Federal de Juiz de Fora

Uppsala University

University of Oslo

University of Copenhagen

IT University of Copenhagen

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THE RUSSIAN CONSTRUCTICON: A NEW LINGUISTIC RESOURCE, ITS DESIGN AND KEY CHARACTERISTICS

Kompʹûternaâ lingvistika i intellektualʹnye tehnologii (2020)

Anna Endresen Valentina Zhukova Daria Mordashova Екатерина Рахилина Olga Lyashevskaya

We present a new open-access electronic resource named the Russian Constructicon that offers a searchable database of Russian constructions accompanied by descriptions of their properties and illustrated with corpus examples. The project was carried out over the period 2016–2020 and at present contains an inventory of over 2200 multi-word constructions of Contemporary Standard Russian. We prioritize “partially schematic” constructions that lie between the two extremes of fully compositional syntactic sequences on the one hand and fully idiomatic (phraseological) expressions on the other hand. Constructions of this type are difficult to account for in terms of either lexicon or grammar alone, and are often underrepresented in reference works of Russian. A typical construction in our database contains a fixed part (anchor words) and an open slot that can be filled with a restricted set of lexemes. In this paper we first focus on key characteristics of this resource that make it different from existing constructicons of other languages. Second, we describe how the new interface will be designed and how it will serve the needs of both linguists and L2 learners of Russian. In particular, we discuss various search possibilities relevant for different users and those parameters that are available for specifying the retrieval output. An example of an entry is given to show how the information about each construction is structured and presented. Third, we provide an overview of our multi-level semantic classification of constructions. We argue that our system of semantic and syntactic tags subdivides our items into meaningful classes and smaller groups and eventually facilitates the identification of constructional families and clusters. This methodology works well in turning the initial list of constructions as unrelated units into a structured network and makes it possible to refine and expand the collected inventory of constructions in a systematic way.

Schematic

10.28995/2075-7182-2020-19-241-255

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Citations (4)

Review of Practices of Collecting and Annotating Texts in the Learner Corpus REALEC

Lecture notes in computer science (2022)

Olga Vinogradova Olga Lyashevskaya

Corpus Linguistics

Text corpus

10.1007/978-3-031-16270-1_7

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Text collections for evaluation of Russian morphological taggers

Journal of Linguistics/Jazykovedný casopis (2017)

Olga Lyashevskaya Victor Bocharov Alexey Sorokin Tatiana Shavrina D. V. Granovsky

Abstract 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 format (Universal Dependencies CONLL-U). The sources of the data were the disambiguated subcorpus of the Russian National Corpus, SynTagRus, OpenCorpora.org data and GICR corpus with the resolved homonymy, all exhibiting different tagsets, rules for lemmatization, pipeline architecture, technical solutions and error systematicity. The collections includes both normative texts (the news and modern literature) and more informal discourse (social media and spoken data), the texts are available under CC BY-NC-SA 3.0 license.

Lemmatisation

10.1515/jazcas-2017-0035

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Citations (7)

Universal Dependencies 2.1

Joakim Nivre Željko Agić Lars Ahrenberg Lene Antonsen María Jesús Aranzabe

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Statistical Word Sense Disambiguation in Contexts for Russian Nouns Denoting Physical Objects

Lecture notes in computer science (2008)

Паничева Полина Mitrofanova Olga Olga Lyashevskaya

Word Sense Disambiguation

Polysemy

Proper noun

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Aspectual Pairs in the Russian National Corpus

Scando Slavica (2011)

Laura A. Janda Olga Lyashevskaya

The status of aspectual pairs formed by prefixation, as in delat´ (imperfective):sdelat´ (perfective) ‘do’ vs. suffixation, as in peredelat´ (perfective):peredelyvat´ (imperfective) ‘redo’ is the topic of a long-standing debate in Russian linguistics. Whereas most scholars assume the same aspectual relation is present for both types of pairs, some (Isačenko, Zaliznjak, Timberlake) hypothesize that only pairs derived via suffixation are true pairs. We present empirical evidence that aspectual pairs behave the same way in terms of the distribution of their forms regardless of whether they are formed via prefixes or suffixes. We examine nearly six million verb forms from the Modern subcorpus of the Russian National Corpus and show that there are no reportable statistical differences between the distributions of forms for perfective and imperfective verbs that can be attributed to the morphology (prefixes vs. suffixes) used to derive paired verbs.

Prefix

10.1080/00806765.2011.631780

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Citations (17)

Accuracy, syntactic complexity and task type at play in examination writing

Studies in corpus linguistics (2022)

Olga Lyashevskaya Olga Vinogradova Anna Scherbakova

This chapter explores the association between syntactic complexity and syntactic accuracy in essays written by Russian learners of English in reply to two examination task types: a description of graphical material (Task 1) and an opinion essay (Task 2). A Poisson regression model served to predict the number of syntactic errors. Two syntactic complexity parameters were statistically significant in predicting syntactic accuracy in both tasks: the numbers of sentences and adverbial clauses. Three more parameters predicted the accuracy in Task 1 only: maximum depth of syntactic trees, and the numbers of adjective + noun and noun + infinitive constructions. Six parameters were related to syntactic accuracy in Task 2: the numbers of all clauses, of tokens and of T- units; the average length of sentence; and the numbers of coordinated and of participle + noun constructions.

Participle

Adjective

Adverbial

10.1075/scl.104.10lya

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Universal Dependencies 1.4

Joakim Nivre Željko Agić Lars Ahrenberg María Jesús Aranzabe Masayuki Asahara

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Citations (60)

Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data