IDENTIFYING NER (NAMED ENTITY RECOGNITION) OBJECTS IN UZBEK LANGUAGE TEXTS

This article discusses NER (Named Entity Recognition) features and detection methods important to the field of NLP. The article describes the concepts of quick word recognition, categorization, understanding of the content of the text, noun, and named object. Methods for automatic identification of named objects from Uzbek texts were presented. NER objects, types and examples corresponding to these types are given in detail on the basis of the table. The opinions of scientists who presented models for identifying NER objects from text abroad, engaged in this scientific work and carried out analysis processes through language corpora were studied. Examples of NER types and classifications were presented. The systems of identifying NER objects in Uzbek texts were analyzed on the basis of dictionaries and grammatical rules, and the ideas were proved by examples. “IOB” and “BILUO” schemes were studied for determining NER objects and their boundaries, and examples were presented. Models for automatically processing the text and identifying NER objects from its content have been presented. At the end of the article, an approximate interface of the program for identifying NER objects in Uzbek language texts (“Uzbek NER analyzer”) was presented. The principle of operation of this program, its content is explained in the interface-based case