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.