К построению инвентаря русских именных конструкций
The paper presents experimental results on automatic construction identification performed on the Russian National Corpus (RNC). For this purpose we developed a toolbox which allows to extract and process co-occurrence data from RNC samples. Russian nouns are chosen as target words. Lists of constructions were built for each target word. By constructions we mean frequent word combinations which include a target word and frequent lexical-semantic tags – context marker of certain meanings of a target word, as well as frequent lemmas representing the given lexical-semantic tags. E.g.: ВИД (kind, sort, type) + r:abstr t:sport: спорт (sport), футбол (football), биатлон (biathlon), etc. Extracted constructions are grouped according to their structure and lexical-semantic content. In conclusion we perform verification of experimental results which implies comparison of lists of constructions with lists of collocations, idioms, etc. registered in various linguistic resources (bigram search engines, dictionaries).
In this monograph the authors assert that Russian verbal prefixes always express meaning, even when they are used to form the perfective partners of aspectual pairs. The prefixes in verbs like написать/na-pisat' 'write' and сварить/s-varit' 'cook' have semantic purpose, even though the corresponding imperfective verbs писать/pisat' 'write' and варить/varit' 'cook' have the same lexical meanings. This suggests a new hypothesis, namely that the Russian verbal prefixes function as verb classifiers, parallel to numeral classifiers.
The exposition is designed to be theory-neutral and accessible to both linguists and nonlinguists. The studies make use of quantitative research on corpus data and statistical models (chisquare, logistic regression, etc.), which are presented in a common-sense way that assumes no special expertise. A user-friendly interactive webpage at http://emptyprefixes.uit.no/book.htm houses links to the authors' database, plus additional data from the studies cited.
This book narrates recent breakthroughs in research on Russian aspect and demonstrates a range of methodologies designed to probe the relationship between the meaning and distribution of linguistic forms. These methodologies are used to investigate the "empty" prefixes, alternating constructions, prefix variation, and aspectual triplets. Though these phenomena have long been known to exist, their extent and behavior have not been previously explored in detail.
The authors propose that the verbal prefixes select verbs according to broad semantic traits, categorizing them the way numeral classifiers categorize nouns. The purpose of the prefixes is to convert amorphous states and activities into discrete events and to group verbs according to the types of events they express. In other words, Russian prefixes are in effect a verb classifier system similar to those proposed for Mandarin Chinese, Hindi-Urdu, and a number of Australian languages, and this hypothesis facilitates cross-linguistic comparisons. The description of Russian prefixes as a verb classifier system furthermore has pedagogical value since curricula may be redesigned to teach students the system according to its meaningful groupings rather than simply requiring them to memorize hundreds of combinations of prefixes with simplex verbs.
In short, the proposal to recognize Russian prefixes as verb classifiers supports the community of people interested in Russian grammar to be better linguists, better instructors, and better learners.
Author presents results of the scientific seminar " Legal regulation of economic activities in China and Russia" (series" Legal aspects of BRICS " ), held in St. Petersburg by the Law Faculty of the Higher School of Economics - St. Petersburg Branch, with a participation of 15 colleagues from 6 universities of China.
The paper differentiates the main reasons of entrepreneurial motivation to start-up, and what supports ability to innovate among entrepreneurs in the Netherlands and Russia.
In many languages of the world, the forms in the irrealis domain (subjunctive, conjunctive, conditional) are also used in complement clauses. The set of verbs that require subjunctive complementation is similar but not identical across languages. The paper identifies Russian verbs licensing subjunctive in complement clauses, either as the only option or as an alternative to the indicative. Basing on the Russian National Corpus, a list of these predicates is compiled, with relative frequencies of subjunctive vs. indicative for each predicate. The main result of the study is distinguishing two types of subjunctive complement clauses. Most predicates belong to the group which is similar to purpose clauses with чтобы, both semantically and syntactically. The subject of the main predicate is involved in the situation described by the subordinate clause by wishing it to be realized, by intention, or causal relations. The second, minor group includes epistemic uses of чтобы with e.g. сомневаться and other predicates in the context of negation, interrogation and other constructions expressing low probability.
A comprehensive theoretical framework for the development of a Semantic Web of a new generation, or of a Multilingual Semantic Web, is outlined. Firstly, the paper grounds the possibility of using a mathematical model being the kernel of the theory of K-representations and describing a system of 10 partial operations on conceptual structures for building semantic representations (or text meaning representations) of, likely, arbitrary sentences and discourses in English, Russian, French, German, and other languages. The possibilities of using SK-languages defined by the theory of K-representations for building semantic annotations of informational sources and for constructing semantic representations of discourses pertaining to biology and medicine are illustrated. Secondly, an original strategy of transforming the existing Web into a Semantic Web of a new generation with the well-developed mechanisms of understanding natural language texts is described. The third subject of this paper is a description of the correspondence between the inputs and outputs of the elaborated algorithm of semantic-syntactic analysis and of its advantages; the semantic representations of the input texts are the expressions of SK-languages (standard knowledge languages). The input texts can be the statements, questions, and commands from the sublanguages of English, Russian, and German. The algorithm has been implemented by means of the programming language PYTHON.
Review of the book by Elena A. Grishina "Russian gestures from a linguistic perspective". Moscow, 2017. 744 p.