This paper explores the distributional characteristics of Uzbek pronouns and adverbs in neural-based POS tagging systems. The study compares BiLSTM-CRF, Transformer (BERT, mBERT, XLM-R), and seq2seq architectures, analyzing contextual dependencies, semantic functions, and embedding representations of pronouns and adverbs. Experimental results demonstrate model efficiency and error typology.
| Mualliflar | Karimova, Zilola, Каримова, Зилола, Karimova, Zilola |
|---|---|
| Jurnal | Хорижий лингвистика ва лингводидактика |
| Nashr sanasi | 2026-02-25 |
| Jild | 4 |
| Son | 2/S |
| Betlar | 76-81 |
| Til | Rus |
| DOI | 10.47689/2181-3701-vol4-iss2/s-pp76-81 |
DOI: 10.47689/2181-3701-vol4-iss2/s-pp76-81 · Maqolaning asl sahifasi
местоимение, наречие, POS-теггинг, дистрибуция, нейронные сети, BERT, морфология, компьютерная лингвистика, pronoun, adverb, POS tagging, distribution, neural network, BERT, morphology, computational linguistics, olmosh, ravish, POS teglash, distributsiya, neyron tarmoq, BERT, morfologiya, kompyuter lingvistikasi
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