Replication data for: Prefix variation in путать: в-. за-, пере- and с-

This case study of the four Natural Perfectives of the Russian simplex verb путать ‘tangle’ sheds light on the following questions: Is it possible to predict the choice of prefix when there is prefix variation in Russian? And if yes, how? Since these questions are particularly relevant for second-language learners, the author also discusses how the present study and similar ones, can be used to make second language learning of Russian more effective. The analysis is based on a database of 630 sentences from the Russian National Corpus (RNC) and takes two factors into consideration: type of construction and semantic category of the internal argument.
The uploaded data contain 3 files: "Database, everything": Each sentence is tagged according to prefix, form of the verb (Active vs Passive), type of construction and semantic category of the internal argument. The four types of constructions and four types of semantic categories are explained with examples from the database inside the article. "Database_simplified": This version of the database contains the three parameters for the sentences: prefix, type of construction and semantic category of the internal argument. The simplified database was created to do statistical analyses in R. "R_putat": The R script that was used in order to produce the cTree which is presented in the article.

本案例研究探讨了俄语简单动词“ путать”（tangle）的四种自然完美式，旨在解答以下问题：在俄语中存在前缀变化时，是否能够预测前缀的选择，以及如果可以，该如何预测？鉴于这些问题对二语学习者尤其重要，作者还讨论了本研究及其类似研究如何被应用于提高俄语二语学习的有效性。分析基于俄罗斯国家语料库（RNC）中的630个句子数据库，并考虑了两个因素：句法结构类型和内部论元的语义类别。上传的数据包含三个文件：
"Database, everything": 每个句子根据前缀、动词形式（主动语态与被动语态）、句法结构类型和内部论元的语义类别进行标记。文章中通过数据库中的示例解释了四种句法结构和四种语义类别。
"Database_simplified": 该数据库版本包含句子的三个参数：前缀、句法结构类型和内部论元的语义类别。简化版数据库的创建是为了在R中进行统计分析。
"R_putat": 用于生成文章中展示的cTree的R脚本。