POS-tagging to highlight the skeletal structure of sentences

2024/11/21 by Grigorii Churakov, Churakov, Grigorii
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling

paper · pdf · doi:10.48550/arxiv.2411.14393

openalex publication_date 2024/11/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This study presents the development of a part-of-speech (POS) tagging model to extract the skeletal structure of sentences using transfer learning with the BERT architecture for token classification. The model, fine-tuned on Russian text, demonstrating its effectiveness. The approach offers potential applications in enhancing natural language processing tasks, such as improving machine translation. Keywords: part of speech tagging, morphological analysis, natural language processing, BERT.

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