Truth Validation with Evidence

TL;DR

This paper presents a system that validates the truthfulness of statements using knowledge graphs and ontologies, providing supporting evidence for false claims with high accuracy.

Contribution

It introduces a novel inference method combining knowledge graphs and ontologies to verify statements and extract evidence of falseness.

Findings

High accuracy in truth validation

Effective evidence extraction for false statements

Knowledge graph quality impacts system performance

Abstract

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.