Systems and Methods for Determining Semantic Roles of Arguments in Sentences

Number: 20170337474
Published: 2017-11-23
Filed: 2016-05-20
Assignee: Disney Enterprises, Inc.
Inventors: Li; Boyang et al.
CPC: G06F16/355; G06F40/30; G06F40/35; G06N20/00; G06N5/02
Verdict: Set aside generic NLP - semantic roles of sentence arguments
Source: Google Patents · FreePatentsOnline

Abstract

There is provided a system including a non-transitory memory storing an executable code and a hardware processor executing the executable code to receive an input sentence including a first predicate and at least a first argument depending from the first predicate, identify the first predicate, identify the first argument based on the first predicate, apply a dependency multiplication to determine a semantic role of the first argument based on the first predicate, and assign the first argument to an argument cluster including one or more similar arguments based on the semantic role of the first argument.

Background

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a diagram of an exemplary system for determining semantic roles ofarguments in sentences, according to one implementation of the present disclosure;

FIG. 2 shows a diagram of an exemplary model for determining semantic roles of arguments in sentences, according to one implementation of the present disclosure;

FIG. 3 showsa diagram of another exemplary model for determining semantic roles of arguments in sentences, according to one implementation of the present disclosure;

FIG. 4 shows a diagram of an exemplary sentence with dependency labels for use with the system of FIG. 1, according to one implementation of the present disclosure;

FIG. 5 shows a table including a plurality of exemplary predicates and arguments determined using the system of FIG. 1, according to one implementation of the present disclosure; and

FIG. 6 shows a flowchart illustrating an exemplary method of determining semantic roles of arguments in sentences, according to one implementation of the present disclosure.DETAILED DESCRIPTION

The following description contains specific information pertaining to implementations in the present disclosure. The drawings in the present application and their accompanying detailed description are directed to merely exemplary implementations. Unless noted otherwise, like or corresponding elements among the figures may be indicated by like or corresponding reference numerals. Moreover

Claims

1. A system comprising: a non-transitory memory storing an executable code; a hardware processor executing the executable code to: receive an input sentence including a first predicate and at least a first argument dependingfrom the first predicate; identify the first predicate; identify the first argument basedon the first predicate; apply a dependency multiplication to determine a semantic role ofthe first argument based on the first predicate; and assign the first argument to an argument cluster including one or more similar arguments based on the semantic role of the first argument. 11. A method for use with a system including a non-transitory memory and a hardware processor, the method comprising: receiving, using the hardware processor, an inputsentence including a first predicate and at least a first argument depending from the first predicate; identifying, using the hardware processor, the first predicate; identifying,using the hardware processor, the first argument based on the first predicate; applying, using the hardware processor, a dependency multiplication to determine a semantic role of the first argument based on the first predicate; and assigning, using the hardware processor, the first argument to an argument cluster including one or more similar arguments based on the semantic role of the first argument.