Learner corpora: relevant information and an overview of the existing frameworks

In the modern world, there is a constant interest in foreign languages. Therefore, the question of learning about the language used by non-native speakers of a certain language, as well as describing their mistakes is a highly relevant matter. Learner corpora differ not only according to the languages they focus on, but also in relation to a number of their properties. The purpose of the study is to present a review the learner corpora available for different languages, as well as to compare the approaches that exist for their annotation. The paper considers the origins of learner corpus research, focuses on the main the stages of a project, types of learner corpora (which may differ in their tasks, students’ mother tongue, language proficiency, text genre, data type, etc.), linguistic and metatextual information that accompany texts and provides a classification of errors. The paper gives a brief overview of annotation tools and corpus platforms that can be used for building a learner corpus.