Dataset of Named Entity Recognition for Uzbek language (11,000+)

As part of the study, an annotated corpus of the Uzbek language was created for training and evaluating named entity recognition models. The corpus includes 11,634 sentences (99408 words) collected from various sources:
• Legislative acts and legal documents: The bulk of the data was extracted from the publicly available lex.uz database, which contains official texts that are highly literate and have a formal language structure.
• Manually created sentences: To increase the number of named entities in sentences and ensure diversity, author's sentences were developed containing several entities of different types. This enriched the corpus with complex structures and increased the efficiency of model training.
Data annotation was carried out manually using the BIOES scheme, which provides detailed marking of boundaries and types of named entities. All abstracts were reviewed by Uzbek language experts to ensure accuracy and consistency of data.