1. A method comprising: identifying, by a processor, a set of training texts; extracting, by the processor, a respective set of features for each of the training texts; training, by the processor, a classification model using the training texts and the extracted features; extracting, by the processor, a token from a natural language text; identifying, by the processor, a set of token attributes associated with the token based on a semantic-syntactic analysis of the natural language text, wherein the set of token attributes comprises at least one of a lexical attribute, a syntactic attribute, or a semantic attribute, and wherein the semantic-syntactic analysis of the natural language text comprises: generating, by the processor, a lexical-morphological structure of a sentence of the natural language text; identifying, by the processor, a syntactic tree using the lexical-morphological structure; generating, by the processor, a language-independent semantic structure based on the syntactic tree; and identifying, by the processor, the set of token attributes using the language-independent semantic structure; determining, by the processor, a category for the token based on the trained classification model and the set of token attributes; and generating, by the processor, a tagged representation of at least part of the natural language text, the tagged representation referencing the category for the token.