124

Tabiiy tillarni qayta ishlash jarayonlaridan biri matnlarni semantik tahlil qilishdir. Matnlar tarkibidagi omonim so‘zlarni ajratib, ularning ma’nolarini farqlash semantik tahlilning muhim vazifasi sanaladi. Omonim so‘zlarni semantik tahlil qilish maqsadida ular turkumlar doirasida uchrashiga ko‘ra 2 ta so‘z turkumi doirasidagi omonimlar, 3 ta so‘z turkumi doirasidagi omonimlar va 4 ta so‘z turkumi doirasidagi omonimlar kabi guruhlarga ajratiladi. O‘zbek tilidagi 3 ta so‘z turkumi doirasida omonimlik hosil qiluvchi so‘zlar 11 ta guruhga ajratiladi. Maqolada o‘zbek tilidagi sifat ˅ ot ˅ ravish, ot ˅ olmosh ˅ fe’l, ot ˅ sifat ˅ fe’l, ot ˅ fe’l ˅ ravish, ot ˅ sifat ˅ predikativ so‘z, ot ˅ ravish ˅ taqlid so‘z, ot ˅ undov ˅ taqlid so‘z, ot ˅ sifat ˅ ko‘makchi, ot ˅ son ˅ fe’l, ot ˅ fe’l ˅ taqlid so‘z, undov so‘z ˅ fe’l ˅ ravish guruhlarga mansub omonim so‘zlarni farqlovchi lingvistik omillar tahlil qilinib, jami 7 ta matematik model ishlab chiqilgan.

  • O'qishlar soni124
  • Nashr sanasi24-02-2022
  • Asosiy tilO'zbek
  • Sahifalar150-161
Ўзбек

Tabiiy tillarni qayta ishlash jarayonlaridan biri matnlarni semantik tahlil qilishdir. Matnlar tarkibidagi omonim so‘zlarni ajratib, ularning ma’nolarini farqlash semantik tahlilning muhim vazifasi sanaladi. Omonim so‘zlarni semantik tahlil qilish maqsadida ular turkumlar doirasida uchrashiga ko‘ra 2 ta so‘z turkumi doirasidagi omonimlar, 3 ta so‘z turkumi doirasidagi omonimlar va 4 ta so‘z turkumi doirasidagi omonimlar kabi guruhlarga ajratiladi. O‘zbek tilidagi 3 ta so‘z turkumi doirasida omonimlik hosil qiluvchi so‘zlar 11 ta guruhga ajratiladi. Maqolada o‘zbek tilidagi sifat ˅ ot ˅ ravish, ot ˅ olmosh ˅ fe’l, ot ˅ sifat ˅ fe’l, ot ˅ fe’l ˅ ravish, ot ˅ sifat ˅ predikativ so‘z, ot ˅ ravish ˅ taqlid so‘z, ot ˅ undov ˅ taqlid so‘z, ot ˅ sifat ˅ ko‘makchi, ot ˅ son ˅ fe’l, ot ˅ fe’l ˅ taqlid so‘z, undov so‘z ˅ fe’l ˅ ravish guruhlarga mansub omonim so‘zlarni farqlovchi lingvistik omillar tahlil qilinib, jami 7 ta matematik model ishlab chiqilgan.

Русский

Одним из процессов обработки естественного языка является семантический анализ текстов. Важной задачей семантического анализа является различение значений слов в тексте. В целях семантического анализа омонимичных слов они делятся на группы, такие как омонимы в пределах двух частей речи, омонимы в пределах трех частей речи и омонимы в пределах четырех частей речи в зависимости от их встречаемости в пределах категорий. В узбекском языке слова, образующие омонимы, делятся на 11 групп в пределах трех частей речи. В данной статье анализируются лингвистические факторы, дифференцирующие слова-омомонимы в узбекском языке, такие как прилагательное ˅ существительное ˅ наречие, существительное ˅ местоимение ˅ глагол, существительное ˅ прилагательное ˅ глагол, существительное ˅ глагол ˅ местоимение, существительное ˅ прилагательное ˅ сказуемое слово, существительное ˅ наречие ˅ имитационное слово, существительное ˅ восклицательное слово ˅ имитационное слово, существительное ˅ прилагательное ˅ вспомогательное, существительное ˅ число ˅ глагол, существительное ˅ глагол ˅ имитационное слово, восклицательное слово ˅ глагол ˅ наречие, что развивает в общей сложности 7 математических моделей.

English

One of the processes of natural language processing is a semantic analysis of texts. An important task of a semantic analysis is to distinguish meanings of words within a text from their meanings. For the purpose of semantic analysis of homonymous words, they are divided into groups such as homonyms within 2 parts of speech, homonyms within 3 parts of speech and homonyms within 4 parts of speech according to their occurrence within categories. In the Uzbek language, words that form a homonym are divided into 11 groups within 3 parts of speech. This article analyzes linguistic factors that differentiate homonymic words in the Uzbek language, such as adjective ˅ noun ˅ adverb, noun ˅ pronoun ˅ verb, noun ˅ adjective ˅ verb, noun ˅ verb ˅ pronoun, noun ˅ adjective ˅ predicate word, noun ˅ adverb ˅ imitation word, noun ˅ exclamation word ˅ imitation word, noun ˅ adjective ˅ auxiliary, noun ˅ number ˅ verb, noun ˅ verb ˅ imitation word, exclamation word ˅ verb ˅ adverb develops a total of 7 mathematical models.

Muallifning F.I.Sh. Lavozimi Tashkilot nomi
1 Elov B.B. texnika fanlari nomzodi (PhD), “Kompyuter lingvistikasi va raqamli texnologiyalar” kafedrasi mudiri Alisher Navoiy nomidagi Toshkent davlat o‘zbek tili va adabiyoti universiteti
2 Ahmedova X.I. tayanch doktorant Alisher Navoiy nomidagi Toshkent davlat o‘zbek tili va adabiyoti universiteti
Havola nomi
1 OndreyP., Miloslav K. UlsaNA [Universal language semantic analyzer]. International Conference Recent Advances in Natural Language Processing. RANLP, 2019. DOI: 10.26615/978-954-452-056- 4_112/.
2 Goyal Ch. Part 9: Step by Step Guide to Master NLP – Semantic Analysis. Available at: https://www. analyticsvidhya.com/blog/2021/06/part-9-step-by-step-guide-to-master-nlp-semantic-analysis/.
3 Kustova G.I., Lyashevskaya O.N., Paducheva E.V., Rakhilina E.V. Semanticheskaya razmetka leksiki v Nasionalnom korpuse russkogo yazyka: prinsipy, problemy, perspektivy [Semantic markup of vocabulary in the National Corpus of the Russian language: principles, problems, prospects]. National Corpus of the Russian Language, 2003-2005. Results and prospects. Moscow, Indrik, 2005, pp. 155-174 .
4 Kobrisov B.P., Kustova G.I., Lyashevskaya O.N., Shemanaeva O.Yu. Rakhilina E.V., Mnogoznachnost kak prikladnaya problema: semanticheskaya razmetka v Nasionalnom korpuse russkogo yazyka [Ambiguity as an applied problem: semantic markup in the National Corpus of the Russian language]. Computational Linguistics and Intelligent Technologies: Proceedings of the International Conference “Dialogue-2006”. Moscow, 2006, pp. 445-450 .
5 Kukanova V.V. Prinsipy semanticheskoi razmetki nasionalnogo korpusa kalmyskogo yazyka [Principles of semantic markup of the national corpus of the Kalmyk language]. Available at: http:// kalmcorpora.ru/sites/default/files/kukanova_25.pdf/.
6 Kretov A.A. Analysis of semantic labels in the NKRS. Available at: http://ruscorpora.ru/ sbornik2008/11.pdf/.
7 Аникин А.Е. Opyt semanticheskogo analiza praslavyanskoi omonimii na indoevropeiskom fone [The experience of the semantic analysis of Proto-Slavic homonymy against the Indo-European background]. Abstract of PhD thesis. Мoscow, 1983.
8 Ermolaeva I.E. Semanticheskoe varirovanie dialektnogo slova v russkikh govorakh Bashkirii: V svyazi s problemoi razgranicheniya polisemii i omonimii [Semantic variation of the dialect word in the Russian dialects of Bashkiria: In connection with the problem of distinguishing between polysemy and homonymy]. Abstract of PhD thesis. 2000.
9 Abjalova M.A. O‘zbek tilidagi matnlarni tahrir va tahlil qiluvchi dasturning lingvistik modullari (Rasmiy va ilmiy uslubdagi matnlar tahriri dasturi uchun) [Linguistic modules of the program for editing and analyzing texts in the Uzbek language (for the program of editing texts in the official and scientific style)]. PhD thesis. Fergana, 2019, 164 p.
10 Ahmedova D. Atov birliklarini o‘zbek tili korpuslari uchun leksik-semantik teglashning lingvistik asos va modellari [Linguistic bases and models of lexical-semantic tagging of Atov units for Uzbek language corpora]. PhD thesis. Bukhara, 2020, 163 p.
11 Hamroyeva Sh. O‘zbek tili mualliflik korpusini tuzishning lingvistik asoslari [Linguistic bases of Uzbek language authorship corps]. PhD thesis. Karshi, 2018, 250 p.
12 Xoliyorov O‘. O‘zbek tili ta’limiy korpusini tuzishning lingvistik asoslari [Linguistic bases of formation of Uzbek language educational corps]. Abstract of PhD thesis. Termez, 2021, pp. 16-52.
13 Gulyamova Sh.Q., Ahmedova X.I. O‘zbek tili semantik analizatori uchun omonim so‘zlar ma’lumotlar bazasini shakllantirish masalasi xususida [On the formation of a database of homonymous words for the semantic analyzer of the Uzbek language]. So‘z san’ati xalqaro jurnali – International Journal of Word Art, Tashkent, 2021, vol. 4, iss. 3, pp. 326-334. DOI: 10.26739/2181- 9297/.
14 Axmedova X.I. Mathematical models that distinguish homonymy in the framework of a word series. Electronic journal of actual problems of modern science, education and training, 2021, October, no. 10/1. ISSN 2181-9750/.
15 Koptelov A.K. Biznes-trener. BPMN dlya resheniya analiticheskikh zadach [Business coach. BPMN for solving analytical problems]. Available at: https://www.omg.org/spec/BPMN/2.0/PDF/.
16 Object Management Group Business Process Model and Notation. Available at: https://www. bpmn.org/.
17 Gulyamova Sh.Q. Semantik analizatori uchun omonimlikni farqlash omillarining ayrim masalalari xususida [On some issues of homonymous differentiation factors for the semantic analyzer]. Promising youth of Uzbekistan. Republican scientific-practical conference, no. 6.
18 Anastasia M., Vladimir M. Mathematical model of an ontological-semantic analyzer using basic ontological-semantic patterns. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017. DOI: 10.1007/978-3-319-62434- 1_5/.
19 Rakhilina E.V., Kustova G.I., Lyashevskaya O.N., Reznikova T.I., Shemanova O.Yu. Zadachi i prinsipy semanticheskoi razmetki leksiki v NKRYa [Tasks and principles of semantic markup of vocabulary in the NCRL]. National corpus of Russian language: 2006-2008. New results and perspectives. Ed. V.A.Plungyan. St. Petersburg, Nestor-Istoriya, 2009, pp. 215-239 .
20 Andrey K., Ilona K. Clustering of word contexts as a method of eliminating polysemy of words]. Proceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019. DOI: 10.1109/EIConRus.2019.8656851/.
21 Bona J.P., Ceusters W. Mismatches between major subhierarchies and semantic tags in SNOMED CT. Journal of Biomedical Informatics, 2018. DOI: 10.1016/j.jbi.2018.02.009/.
22 Lyashevskaya O.N. Topologicheskie klassy imen v semanticheskoi razmetke Nasionalnogo korpusa russkogo yazyka [Topological classes of names in the semantic markup of the National Corpus of the Russian language]. Corpus Linguistics-2008. Trudy mejdunarodnoy konferensii. St. Petersburg, 2008б October 6-10. St. Petersburg State University, 2008, pp. 276-284.
23 Kobrisov B.P., Lyashevskaya O.N., Shemanaeva O.Yu. Poverkhnostnye filtry dlya razresheniya semanticheskoi omonimii v tekstovom korpuse [Surface filters for resolving semantic homonymy in a text corpus].
24 Kobrisov B.P. Modeli mnogoznachnosti russkoi predmetnoi leksiki: globalnye i lokalnye pravila razresheniya omonimii [Models of the ambiguity of Russian subject vocabulary: global and local rules for resolving homonymy]. Abstract of PhD thesis. Мoscow, Russian State University for the Humanities, 2004.
25 Kusal K. Formal’nye i semanticheskie sblizheniya v sfere russko-pol’skoi mezh”yazykovoi omonimii [Formal and semantic convergence in the field of Russian-Polish interlingual homonymy]. Studia Rossica Posnaniensia, 2021, no. 46 (1), pp. 101-114. DOI: 10.14746/strp.2021.46.1.8/.
26 Kobozeva I.M., Narinyani A.S., Selegei V.P. Kompyuternaya lingvistika i intellektualnye tekhnologii [Computational Linguistics and Intelligent Technologies]. Proceedings of the international conference Dialogue 2005. Мoscow, 2005.
Kutilmoqda