опрацювання природньої мови

The problem of automated error detection in Ukrainian texts is becoming particularly relevant in the context of the growth of digital content. A mathematical model of a decision support system for detecting errors in Ukrainian-language texts has been developed. The process of error identification has been studied as a multi-class classification task at the token level, considering the context of the text. The use of probabilistic models has been proposed to determine the type of error depending on the environment of tokens in the text.

This article is dedicated to the study and analysis of grammatical error correction (GEC) tasks in Ukrainian language texts, which is a significant issue in the field of natural language processing (NLP). The paper addresses the specific challenges faced by automatic error correction systems due to the peculiarities of the Ukrainian language, such as its morphological complexity and contextuality. Examples of typical errors are provided, and the reasons why existing GEC methods often prove insufficient for Ukrainian are analysed.