machine learning

This paper describes the experiments for the task on information extraction from news texts in Russian in a setting with a wide variety of types of entities and relations. We have adapted the SpERT model which uses the BERT network as a core for the joint extraction of entities and...

The Russian language has an inflective structure and does not have a strict word order, which generates processing problems such as part-of-speech homonymy. The paper addresses this issue. The existing approaches to resolving the morphological homonymy problem can be divided into the following groups: rule-based approaches, statistical approaches, machine learning...