Replication Data for: Predicting Russian aspect by frequency across genres
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. 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 addit' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["aspect","correspondence analysis","frequency","Russian","semantics","verbs"]} <|eot_id|>
 Here is the Description of a dataset. 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 addit' . Please return only a json list of at most 3 Keywords corresponding to the 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 addit
aspect; correspondence analysis; frequency; Russian; semantics; verbs