1. A method comprising: extracting, by a processor, tokens from an untagged corpus of texts; generating, by the processor, a set of attributes for each of the tokens based at least on a deep semantic-syntactic analysis, wherein the set of attributes comprise lexical, syntactic, and semantic attributes; selecting, by the processor, a subset of the attributes for each of the tokens; retrieving, by the processor, classifier attributes and categories based on a trained model, wherein the classifier attributes are related to one or more categories; comparing, by the processor, the subset of the attributes for each of the tokens with the classifier attributes; classifying, by the processor, each of tokens to at least one of the categories based on the comparing; and generating, by the processor, tagged text based on the categorized tokens.