DaNetQA, a new question-answering corpus, follows BoolQ [2] design: it comprises natural yes/no questions. Each question is paired with a paragraph from Wikipedia and an answer, derived from the paragraph. The task is to take both the question and a paragraph as input and come up with a yes/no answer, i.e. to produce a binary output. In this paper, we present a reproducible approach to DaNetQA creation and investigate transfer learning methods for task and language transferring. For task transferring we leverage three similar sentence modelling tasks: 1) a corpus of paraphrases, Paraphraser, 2) an NLI task, for which we use the Russian part of XNLI, 3) another question answering task, SberQUAD. For language transferring we use English to Russian translation together with multilingual language fine-tuning.

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The article is devoted to the study of a fragment of the Russian linguistic picture of the world associated with the phenomenon of “city”, as well as the problem of the formation of ideas about modern Russian cities in the minds of foreigners studying Russian. The aim of the work is to reconstruct the frame model of the concept “city”, as well as to identify the linguocultural, lexical and grammatical resources of this concept. The use of cognitive structures in creating the image of a city demonstrates the possibility of applying the methods of cognitive linguistics in didactics. The author focuses on knowledge and ideas related to the concept of “city”, which are reflected in the texts of textbooks on Russian as a foreign language. The study of fragments of the Russian linguistic picture of the world contributes to the formation of linguistic-cultural and socio-cultural competencies of students.