TY - GEN

T1 - Developing Rule-Based and Gazetteer Lists for Named Entity Recognition in Uzbek Language: Geographical Names

AU - Mengliev, Davlatyor B.

AU - Barakhnin, Vladimir B.

AU - Atakhanov, Mukhammadjon

AU - Ibragimov, Bahodir B.

AU - Eshkulov, Mukhriddin

AU - Saidov, Bobur

N1 - Conference code: 16

PY - 2023

Y1 - 2023

N2 - Named entity recognition is one of the current problems in the field of natural language processing, especially for languages with limited resources, where the Uzbek language is one of them. In this scientific work, the authors conduct a review study and also propose a practical solution for recognizing named entities in the Uzbek language. The proposed approach is designed and operated on the basis of gazetteer rules and lists, with special emphasis on the identification of place names. The authors do not use machine learning methods due to limited linguistic resources, which makes the proposed approach easy to implement and fast to scale. The cornerstone of the proposed approach is two algorithms, where the first algorithm, based on morphological analysis, despite its simplicity, is somewhat limited in its capabilities. Conversely, the second algorithm is based on the syntactic analysis of texts in the Uzbek language and offers a more flexible approach to recognizing named entities. Both algorithms use a specific set of rules obtained as a result of a detailed study of the structure of the Uzbek language and its morphological and grammatical features. The purpose of this study is to enrich the relatively sparse literature on named entity recognition in the Uzbek language and to provide a solid basis for continued research in this area.

AB - Named entity recognition is one of the current problems in the field of natural language processing, especially for languages with limited resources, where the Uzbek language is one of them. In this scientific work, the authors conduct a review study and also propose a practical solution for recognizing named entities in the Uzbek language. The proposed approach is designed and operated on the basis of gazetteer rules and lists, with special emphasis on the identification of place names. The authors do not use machine learning methods due to limited linguistic resources, which makes the proposed approach easy to implement and fast to scale. The cornerstone of the proposed approach is two algorithms, where the first algorithm, based on morphological analysis, despite its simplicity, is somewhat limited in its capabilities. Conversely, the second algorithm is based on the syntactic analysis of texts in the Uzbek language and offers a more flexible approach to recognizing named entities. Both algorithms use a specific set of rules obtained as a result of a detailed study of the structure of the Uzbek language and its morphological and grammatical features. The purpose of this study is to enrich the relatively sparse literature on named entity recognition in the Uzbek language and to provide a solid basis for continued research in this area.

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85182260437&origin=inward&txGid=630252184d4a93ab900d86c2626103a4

UR - https://www.mendeley.com/catalogue/efc76d86-9df0-32ca-a425-fe56fa36a6b6/

U2 - 10.1109/apeie59731.2023.10347697

DO - 10.1109/apeie59731.2023.10347697

M3 - Conference contribution

SN - 9798350330885

SP - 1500

EP - 1504

BT - Proceedings of the 2023 IEEE 16th International Scientific and Technical Conference Actual Problems of Electronic Instrument Engineering, APEIE 2023

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument Engineering

Y2 - 10 November 2023 through 12 November 2023

ER -