Abstract
Due to the fact that the development of the corpus has become one of the priorities for all languages of the modern world, the improvement of the national corpus of the Kazakh language (NCKL) is also a very relevant issue. One of the types of linguistic information reflecting the meaning of a word in the NCKL database is lexical-semantic markup. The article examines the world experience of lexical-semantic markup and provides an overview of foreign research. Analyzing the national corpus of the Russian language and the Kalmyk language, the peculiarities of the national corpus of the Kazakh language are noted. The methods of dividing verbs into lexical-semantic groups are indicated, on the basis of which the markup of the corpus is formed, i.e. the definition of codes that reveal the meaning of the word. In the study, lexical-semantic groups were classified according to the method of describing verb meanings and synthesizing based on common meanings, semantic groups of Kazakh verbs were compared with each other and with semantic groups in other languages. As a result of the research, macro- and microgroups characterizing the meaning of the verb were included in the National Corpus of the Kazakh language. In total, 100 lexical-semantic groups have been formed. The lexical-semantic markup of verbs included six different codes. Lexical-semantic markup was attached to 18200 verbs based on the corpus. The compiled lexical-semantic markup expands the information about the word in the National Corpus of the Kazakh language, allows the user to easily determine the meaning of the word, sort verbs with a similar meaning and verbs with a positive, negative connotation of meaning. It can be said that lexical-semantic markup is one of the first steps to facilitate the recognition of the semantics of words of Kazakh artificial intelligence, which is expected to be created in the near future.