International Business Machines Corporation
Increasing the accuracy of a statement by analyzing the relationships between entities in a knowledge graph

Abstract:

A cognitive system improves the accuracy of a natural language statement by analyzing relationships between entities in a knowledge graph for the statement. A natural language processing engine extracts entities and relationships in the statement, and a yes/no pipeline gauges the accuracy of the statement. If a statement is deemed inaccurate, the knowledge graph is used to identify a predominant relationship between certain entities, and a candidate phrase representing the predominant relationship is generated and presented to the user as a suggested replacement for a target phrase in the statement representing the relationship. The yes/no pipeline computes an accuracy score for the statement, and the statement is deemed inaccurate when the score is below a programmable threshold. The assertiveness of the system can be tuned by requiring the accuracy score of a proposed modified statement to be greater than the score of the original statement plus some tuning factor.