research data . Dataset . 2017

Replication Data for: Predicting Russian aspect by frequency across genres

Eckhoff, Hanne; Janda, Laura; Lyashevskaya, Olga Nikolayevna;
Open Access
  • Published: 01 Jan 2017
  • Publisher: DataverseNO
Abstract
We ask whether the aspect of individual verbs can be predicted based on the statistical distribution of their inflectional forms and how this is influenced by genre. To address these questions, we present an analysis of the “grammatical profiles” (relative frequency distributions of inflectional forms) of three samples of verbs extracted from the Russian National Corpus, representing three genres: Journalistic prose, Fiction, and Scientific-Technical prose. We find that the aspect of a given verb can be correctly predicted from the distribution of its forms alone with an average accuracy of 92.7%. Remarkably, this accuracy is statistically indistinguishable from the accuracy of prediction of aspect based on morphological marking. We maintain that it would be possible for first language learners to use distributional tendencies, in addition to morphological and other cues (for example semantic and syntactic cues), in acquiring the verbal category of aspect in Russian.
Persistent Identifiers
Fields of Science and Technology classification (FOS)
06 humanities and the arts, 0602 languages and literature, 060201 languages & linguistics
Subjects
free text keywords: Arts and Humanities, semantics, aspect, correspondence analysis, Russian, verbs, frequency
Communities
  • Digital Humanities and Cultural Heritage
  • Social Science and Humanities
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