Semantic processor for recognition of cause-effect relations in natural language documents
First Claim
1. A method for recognizing cause-effect relations in natural language documents to generate a cause-effect knowledge base comprising:
- providing text from at least one natural language document;
recognizing one or more expanded Subject-Action-Object (eSAO) sets in the text, wherein each eSAO set has one or more eSAO components;
matching the one or more eSAO sets against cause-effect relationship patterns;
generating one or more eSAO cause-effect relations based on the matching, wherein the eSAO cause-effect relation comprises a cause eSAO and an effect eSAO; and
storing the one or more eSAO cause-effect relations in a knowledge base.
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Abstract
A Semantic Processor for the recognition of Cause-Effect relations in natural language documents which includes a Text Preformatter, a Linguistic Analyzer and a Cause-Effect Knowledge Base Generator. The Semantic Processor provides automatic recognition of cause-effect relation both inside single fact and between the facts in arbitrary text documents, where the facts are also automatically extracted from the text in the form of seven-field semantic units. The recognition of Cause-Effect relations is carried out on the basis of linguistic (including semantic) text analysis and a number of recognizing linguistic models built in the form of patterns.
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Citations
22 Claims
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1. A method for recognizing cause-effect relations in natural language documents to generate a cause-effect knowledge base comprising:
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providing text from at least one natural language document;
recognizing one or more expanded Subject-Action-Object (eSAO) sets in the text, wherein each eSAO set has one or more eSAO components;
matching the one or more eSAO sets against cause-effect relationship patterns;
generating one or more eSAO cause-effect relations based on the matching, wherein the eSAO cause-effect relation comprises a cause eSAO and an effect eSAO; and
storing the one or more eSAO cause-effect relations in a knowledge base. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A semantic processor for recognizing cause-effect relations in text in electronic or digital form comprising:
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a linguistic knowledge base; and
a semantic analyzer comprising;
an expanded subject-action-object (eSAO) recognizer for producing one or more eSAO sets based on the text, wherein the eSAO sets are based on eSAO definitions stored in the linguistic knowledge base; and
a cause-effect recognizer for matching the one or more eSAO sets with known cause-effect relationship patterns stored in the linguistic knowledge base and producing one or more eSAO cause-effect relations based on the match, whereby the one or more eSAO cause-effect relations are stored in a knowledge base for later use. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22)
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Specification