Truth Validation with Evidence
This addresses the issue of unreliable information sources for users needing verified content, but it appears incremental as it builds on existing knowledge graph methods.
The authors tackled the problem of validating the truthfulness of statements by developing a system that uses knowledge graphs and ontologies to infer truth and provide evidence for false statements, showing very good results with valid and concise evidence.
In the modern era, abundant information is easily accessible from various sources, however only a few of these sources are reliable as they mostly contain unverified contents. We develop a system to validate the truthfulness of a given statement together with underlying evidence. The proposed system provides supporting evidence when the statement is tagged as false. Our work relies on an inference method on a knowledge graph (KG) to identify the truthfulness of statements. In order to extract the evidence of falseness, the proposed algorithm takes into account combined knowledge from KG and ontologies. The system shows very good results as it provides valid and concise evidence. The quality of KG plays a role in the performance of the inference method which explicitly affects the performance of our evidence-extracting algorithm.