Predicting Russian aspect by frequency across genres
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 for...
| Main Authors: | , , |
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| Format: | Journal article |
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Ohio State University
2017
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| _version_ | 1826300351340347392 |
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| author | Eckhoff, H Janda, L Lyashevskaya, O |
| author_facet | Eckhoff, H Janda, L Lyashevskaya, O |
| author_sort | Eckhoff, H |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T05:15:49Z |
| format | Journal article |
| id | oxford-uuid:dd240e71-e321-4506-bf95-1b1ae70f3338 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T05:15:49Z |
| publishDate | 2017 |
| publisher | Ohio State University |
| record_format | dspace |
| spelling | oxford-uuid:dd240e71-e321-4506-bf95-1b1ae70f33382022-03-27T09:23:01ZPredicting Russian aspect by frequency across genresJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:dd240e71-e321-4506-bf95-1b1ae70f3338Symplectic Elements at OxfordOhio State University2017Eckhoff, HJanda, LLyashevskaya, OWe 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. |
| spellingShingle | Eckhoff, H Janda, L Lyashevskaya, O Predicting Russian aspect by frequency across genres |
| title | Predicting Russian aspect by frequency across genres |
| title_full | Predicting Russian aspect by frequency across genres |
| title_fullStr | Predicting Russian aspect by frequency across genres |
| title_full_unstemmed | Predicting Russian aspect by frequency across genres |
| title_short | Predicting Russian aspect by frequency across genres |
| title_sort | predicting russian aspect by frequency across genres |
| work_keys_str_mv | AT eckhoffh predictingrussianaspectbyfrequencyacrossgenres AT jandal predictingrussianaspectbyfrequencyacrossgenres AT lyashevskayao predictingrussianaspectbyfrequencyacrossgenres |