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

  • US 8,478,584 B1
  • Filed: 11/06/2012
  • Issued: 07/02/2013
  • Est. Priority Date: 11/06/2012
  • Status: Expired due to Fees
First Claim
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1. 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.

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