NLP

Data Set Formation Method for Checking the Quality of Learning Language Models of the Transitive Relation in the Logical Conclusion Problem Context

A method for data set formation has been developed to verify the ability of pre-trained models to learn transitivity dependencies. The generated data set was used to test the quality of learning the transitivity dependencies in the task of natural language inference (NLI). Testing of a data set with a size of 10,000 samples (MultiNLI) used to test the RoBerta model.

Information System for Ukrainian Text Voiceover Based on Nlp and Machine Learning Methods

During the research, an information system for voicing Ukrainian-language text was developed based on NLP and machine learning methods. The created information system is implemented in the form of a desktop application, which allows the process of voicing the Ukrainian-language text. The created system included all stages of software development: the design process, the implementation process, and the testing process.

Overview of the Ukrainian language resources within the multilingual European MULTEXT-East project, v. 4

The article presents an overview of computational resources for the Ukrainian language within a multilingual European MULTEXT-East project (MTE, http://nl.ijs.si/ME/V4) freely available for researchers since May 2010, including a formal representation of morphosyntactic specifications consisting of 1239 unique grammatical tags in the XML, TEI-5 compatible, format and a morphosyntactic lexicon covering over 200000 wordforms with lemmas and morphosyntactic codes.