Method and system for domain-optimized semantic tagging and task execution using task classification encoding

A method for performing a task in a natural language processing (NLP) system, comprising:

• processing text to obtain a plurality of numerical encodings, wherein the text comprises a plurality of entities, wherein each of the plurality of numerical encodings is associated with one of the plurality of entities, and wherein the text is derived from an utterance;
• populating a task list with each of the plurality of numerical encodings that have a length less than a pre-determined length;
• populating a variable list with each of the plurality of numerical encodings that have a length greater than a pre-determined length;
• selecting a numerical encoding from the task list, wherein the numerical encoding identifies a task in a domain-specific schema;
• determining that the variable list does not include a variable value required to perform the task;
• generating a sentence to obtain the variable value associated with a variable, wherein the variable is associated with a second numerical encoding, and wherein the second numerical encoding includes the numerical encoding;
• transmitting the sentence to a user device;
• in response to the transmitting, receiving the variable value for the variable in response to the dialogue sentence;
• and
• performing the task using the variable value.