Труды КНЦ (Технические науки вып. 7/2023(14))

15. GitHub — natasha/razdel: Rule-based token, sentence segmentation for Russian language [Электронный ресурс]. URL: https://github.com/natasha/razdel (дата обращения: 18.09.2023). 16. Segalovich I. A fast morphological algorithm with unknown word guessing induced by a dictionary for a web search engine // Proceedings o f the International Conference on Machine Learning; Models, Technologies and Applications. 2003. P. 273-280. 17. Пушкинская энциклопедия: Произведения. Вып. 1. А-Д. СПб.: Нестор-История, 2009. 520 с. 18. История России | История Российской империи с древних времен и по наши дни // Государственный исторический музей [Электронный ресурс]. URL: https://shm.ru/articles/istoriya-rossii/#7 (дата обращения: 18.09.2023). References 1. Humbel M., Nyhan J., Vlachidis A., Sloan K., Ortolja-Baird A. Named-entity recognition for early modern textual documents: a review o f capabilities and challenges with strategies for the future. Journal o f Documentation. Emerald Publishing Limited, 2021, vol. 77, no. 6, pp. 1223-1247. 2. Al-Moslmi T., Ocana M. G., Opdahl A. L., Veres C. Named entity extraction for knowledge graphs: A literature overview. IEEE Access. IEEE, 2020, vol. 8, pp. 32862-32881. 3. Shen W., Li Y., Liu Y., Han J., Wang J., Yuan X. Entity linking meets deep learning: Techniques and solutions. IEEE Transactions on Knowledge and Data Engineering. IEEE, 2021. 4. Elektronnoe nauchnoe izdanie "Pushkin" [Digital scientific edition “Pushkin”]. Fundamental'naya elektronnaya biblioteka “Russkaya literatura i fol'klor” [Fundamental Digital Library. “Russian literature and folklore”], 2002. (In Russ.). Available at: http://feb-web.ru/feb/pushkin/default.asp (accessed: 01.10.2023). 5. Nasar Z., Jaffry S. W., Malik M.K. Named entity recognition and relation extraction: State-of-the-art. ACM Computing Surveys (CSUR). ACM New York, NY, USA, 2021, vol. 54, no. 1, pp. 1-39. 6. GitHub — yandex/tomita-parser. Available at: https://github.com/yandex/tomita-parser/ (accessed: 18.09.2023). 7. GitHub — natasha/yargy: Rule-based facts extraction for Russian language. Available at: https://github.com/natasha/yargy (accessed: 18.09.2023). 8. GitHub — natasha/slovnet: Deep Learning based NLP modeling for Russian language. Available at: https://github.com/natasha/slovnet (accessed: 18.09.2023). 9. Burtsev M. et al. Deeppavlov: Open-source library for dialogue systems. Proceedings o f ACL 2018, System Demonstrations, 2018, pp. 122-127. 10. Honnibal M., Montani I., Van Landeghem S., Boyd A. spaCy: Industrial-strength natural language processing in python. Zenodo, Honolulu, HI, USA, 2020. 11. Hachey B., Radford W., Curran J. R. Graph-based named entity linking with Wikipedia. Web Information System Engineering-WISE 2011: 12th International Conference, Sydney, Australia, October 13-14, 2011. Proceedings 12, 2011, pp. 213-226. 12. Čuljak M., Spitz A., West R., Arora A. Strong heuristics for named entity linking. arXiv preprint arXiv:2207.02824, 2022. 13. Tamper M., Oksanen A., Tuominen J., Hietanen A., Hyvonen E. Automatic annotation service appi: Named entity linking in legal domain. European Semantic Web Conference, 2020, pp. 208-213. 14. Knowledge Base Question Answering (KBQA) — DeepPavlov 1.3.0 documentation. Available at: https://docs.deeppavlov.ai/en/master/features/models/kbqa.html (accessed: 18.09.2023). 15. GitHub — natasha/razdel: Rule-based token, sentence segmentation for Russian language. Available at: https://github.com/natasha/razdel (accessed: 18.09.2023). 16. Segalovich I. A fast morphological algorithm with unknown word guessing induced by a dictionary for a web search engine. Proceedings o f the International Conference on Machine Learning; Models, Technologies and Applications, 2003, pp. 273-280. 17. Pushkinskaya encyclopedia: Proizvedenya (A-D) [Pushkin Encyclopedia: Works A-D]. Saint Petersburg, Nestor-Istoria, 2009, vol. 1, 520 p. (In Russ.). Труды Кольского научного центра РАН. Серия: Технические науки. 2023. Т. 14, № 7. С. 5-15. Transactions of the Kola Science Centre of RAS. Series: Engineering Sciences. 2023. Vol. 14, No. 7. P. 5-15. © Тесля Н. Н., Шутюк В. Д., Жарков В. М., Витязев А. П., Сиповский Г. В., 2023 14