O‘ZBEK TILI OLMOSH VA RAVISHLARINING GRAMMATIK TEGLANISHIDA KONTEKSTGA BOG‘LIQ SEMANTIK NOANIQLIKLARNI AVTOMATIK BARTARAF ETISH MODELLARI

Mualliflar

  • Karimova Zilola ToshDO‘TAU Kompyuter lingvistikasi mutaxassisligi magistranti Muallif

DOI:

https://doi.org/10.65164/htz4xx21

Kalit so‘zlar:

olmosh, ravish, POS teglash, korpus lingvistika, morfologiya

Abstrak

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 

Havolalar

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.

Yuklab olishlar

Nashr qilingan

2025-12-29