Invention Machine Corporation

Invention Machines Corporation

Alexander Vorontsov

James Todhunter

Igor V Sovpel

Dzianis Pastanohau

Alexei Vertel

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.

Semantic processor for recognition of cause-effect relations in natural language documents

A semantic processor and method for automatically recognizing Whole-Part relations in at least one natural language electronic or digital document recognizes one or more expanded Subject-Action-Object (eSAO) sets in text, wherein each eSAO set has one or more eSAO components; matches the one or more eSAO sets against Whole-Part relationship patterns, and generates one or more eSAO Whole-Part relations based on the matching, wherein the eSAO Whole-Part relation comprises a Whole eSAO and an Part eSAO.

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Minsk, Belarus

Alexander Vorontsov