O‘ZBEK TILI OLMOSH VA RAVISHLARINING GRAMMATIK TEGLANISHIDA KONTEKSTGA BOG‘LIQ SEMANTIK NOANIQLIKLARNI AVTOMATIK BARTARAF ETISH MODELLARI
DOI:
https://doi.org/10.65164/htz4xx21Ключевые слова:
olmosh, ravish, POS teglash, korpus lingvistika, morfologiyaАннотация
Ushbu maqola o‘zbek tilidagi leksik birliklar, xususan olmosh va ravish so‘z turkumlarining grammatik POS teglash jarayonidagi murakkabliklarini ilmiy tahlil qiladi. Korpus asosida olmoshlarning kontekstual noaniqligi, ravishlarning darajalanish kategoriyalari va ularning sintaktik moslashuvi o‘rganilgan. Neyron va qoidaviy modellar yordamida teglash aniqligi va samaradorligi solishtiriladi
Библиографические ссылки
1. Sharipov, M., Kuriyozov, E., Yuldashev, O., & Sobirov, O. (2023). UzbekTagger: The rule‑based
POS tagger for Uzbek language.
2. Bobojonova, L., Akhundjanova, A. (2025). BBPOS: BERT‑based Part‑of‑Speech Tagging for
Uzbek.
3. Mansurov, B., & Mansurov, A. (2021). UzBERT: pretraining a BERT model for Uzbek.
4. Sharipov, M., Mattiev, J., Sobirov, J. (2022). Creating a morphological and syntactic tagged
corpus for the Uzbek language.
5. Norboev, B., Rustamov, Sh., & Berdiev, G. (2025). Processing the Uzbek Language Using
Natural Language Processing (NLP) Artificial Intelligence.
6. Kobilov, S. S., Nazarov, J. N., & Rabbimov, I. M. (2025). Achieving Higher Accuracy in
Classifying Uzbek Words into Grammatical Categories Using the CRF Model as Opposed to the
HMM Model.