Ontology driven dictionary generation and ambiguity resolution for natural language processing

  • US 10,268,673 B2
  • Filed: 12/01/2017
  • Issued: 04/23/2019
  • Est. Priority Date: 06/12/2012
  • Status: Active Grant
First Claim
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1. A computer implemented method for natural language processing ambiguity resolution, comprising:

  • storing, in computer memory, an ontological hierarchy of classes and sub-classes, wherein each class or sub-class represents a distinct grammatical function or grammatical property;

    storing, in computer memory, a set of grammatical rules, wherein each grammatical rule stores a permissible positional relation between one class or sub-class and another class or sub-class;

    storing, in computer memory, a dictionary for each class and subclass comprising compiled word instances belonging to the class or sub-class;

    receiving, using a computer processor, a phrase comprising at least two words that are each associated in the dictionary with at least one class and at least two sub-classes;

    annotating, using the processor, the at least two words with possible classes and sub-classes to which the at least two words belong, based on the dictionary; and

    until each of the at least two words is annotated with a single possible class and sub-class;

    eliminating, using the processor, a possible class or sub-class for an ambiguous word of the at least two words, based on the grammatical rules and possible classes or sub-classes of one or more other words in the phrase, andeither selecting, using the processor, a next ambiguous word of the at least two words that remains annotated with more than one possible class and sub-class to be eliminated, or determining, using the processor, that each of the at least two words is annotated with a single possible class and sub-class.

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