Input entity identification from natural language text information
First Claim
Patent Images
1. A device, comprising:
- one or more processors to;
receive text to be processed to identify input entities included in the text;
identify text sections of the text;
generate a list of terms included in the text sections of the text;
perform a feature extraction technique to determine whether each term, in the list of the terms, is an object of an action,the feature extraction technique causing a subject-predicate-object relationship to be extracted from one of the text sections;
perform one or more other feature extraction techniques, on the terms included in the text sections, to identify the input entities included in the text,the one or more other feature extraction techniques including at least one of;
a technique to determine tag patterns for the terms based on tags associated with the terms,a technique to determine whether the terms are capitalized,a technique to determine a headword in each term than includes multiple words,a technique to determine a number of constituent words in each term,a technique to determine semantic similarities of input type actions acting on the terms,a technique to determine semantic similarities of non-input type actions acting on the terms,
the non-input type actions acting on the terms being action terms that are not in the list of terms,a technique to determine a distance of each term from an action appearing in a same text section associated with each term, ora technique to identify surrounding context for each term and associated tags with the surrounding context;
generate information that identifies the input entities included in the text, based on performing the feature extraction technique and the one or more other feature extraction techniques; and
provide the information that identifies the input entities included in the text.
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Abstract
A device may include one or more processors. The device may receive text to be processed to identify input entities included in the text. The device may identify text sections of the text. The device may generate a list of terms included in the text sections of the text. The device may perform one or more feature extraction techniques, on the terms included in the text sections, to identify the input entities included in the text. The device may generate information that identifies the input entities included in the text, based on performing the one or more feature extraction techniques. The device may provide the information that identifies the input entities included in the text.
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Citations
20 Claims
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1. A device, comprising:
one or more processors to; receive text to be processed to identify input entities included in the text; identify text sections of the text; generate a list of terms included in the text sections of the text; perform a feature extraction technique to determine whether each term, in the list of the terms, is an object of an action, the feature extraction technique causing a subject-predicate-object relationship to be extracted from one of the text sections; perform one or more other feature extraction techniques, on the terms included in the text sections, to identify the input entities included in the text, the one or more other feature extraction techniques including at least one of; a technique to determine tag patterns for the terms based on tags associated with the terms, a technique to determine whether the terms are capitalized, a technique to determine a headword in each term than includes multiple words, a technique to determine a number of constituent words in each term, a technique to determine semantic similarities of input type actions acting on the terms, a technique to determine semantic similarities of non-input type actions acting on the terms,
the non-input type actions acting on the terms being action terms that are not in the list of terms,a technique to determine a distance of each term from an action appearing in a same text section associated with each term, or a technique to identify surrounding context for each term and associated tags with the surrounding context; generate information that identifies the input entities included in the text, based on performing the feature extraction technique and the one or more other feature extraction techniques; and provide the information that identifies the input entities included in the text. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A non-transitory computer-readable medium storing instructions, the instructions comprising:
one or more instructions that, when executed by one or more processors, cause the one or more processors to; receive text to be processed to identify input entities included in the text; identify text sections of the text; generate a list of terms included in the text sections of the text; perform a feature extraction technique to determine whether each term, in the list of the terms, is an object of an action, the feature extraction technique causing a subject-predicate-object relationship to be extracted from one of the text sections; perform one or more other feature extraction techniques, on the terms included in the text sections, to identify the input entities included in the text; generate information that identifies the input entities included in the text, based on performing the feature extraction technique and the one or more other feature extraction techniques; and provide the information that identifies the input entities included in the text. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A method, comprising:
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receiving, by a device, text to be processed to identify input entities included in the text; identifying, by the device, text sections of the text; generating, by the device, a list of terms included in the text sections of the text; performing, by the device, a feature extraction technique to determine whether each term, in the list of the terms, is an object of an action, the feature extraction technique causing a subject-predicate-object relationship to be extracted from one of the text sections; performing, by the device, one or more other feature extraction techniques, on the terms included in the text sections, to identify the input entities included in the text, the one or more other feature extraction techniques including at least one of; determining tag patterns for the terms based on tags associated with the terms, determining whether the terms are capitalized, determining a headword in each term than includes multiple words, determining a number of constituent words in each term, determining semantic similarities of input type actions acting on the terms, determining semantic similarities of non-input type actions acting on the terms, the non-input type actions acting on the terms being action terms that are not in the list of terms, determining a distance of each term from an action appearing in a same text section associated with each term, or identifying surrounding context for each term and associating tags with the surrounding context; generating, by the device, information that identifies the input entities included in the text, based on performing the feature extraction technique and the one or more other feature extraction techniques; and providing, by the device, the information that identifies the input entities included in the text. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification