Technology of Semantic Labeling of the Adjective in Uzbek Language

Almost all languages have words that represent some attribute. These are called adjectives (attributes) and their processing is of great importance for natural language processing (NLP). A database of semantically and grammatically tagged adjectives is needed for text generation, automatic annotation, machine translation, tone analysis, language corpora, thesauri and language ontologies. In this article, the technology of semantic labeling of adjective (attribute) in Uzbek language is analyzed. In the field of NLP, semantic tagging is one of the important aspects of classifying words in texts in terms of meaning and determining their logical relationships. In the article, both grammatical and semantic features of the adjective word type are considered, and modern methods of classifying such words are analyzed - in particular, machine learning (ML) algorithms, neural networks and semantic tagging models based on linguistic rules. In addition, semantic tagging challenges that may arise due to the unique grammatical and morphological structure of the Uzbek language and solutions to them are discussed. In the article, 13,445 words of the adjective genre taken from the corpus www.uzcorpora.uz are analyzed grammatically and semantically, and the stages of semantic tagging of these words are explained in detail. The results of this research are useful for the further development of the semantic tagging process, for the advancement of language technologies, and for various applications, such as automatic translation, semantic indexing of texts, and artificial intelligence systems.

Ҳали таржима қилинмаган