ReVera Framework: A Framework for Fact Checking Traceability

Abstract

Professional fact-checking tends to be costly and scalability challenging. For this reason, a series of methods to automate this process has been emerging. Unfortunately, these methods have been created with monolithic architectures, not making use of pre-built parts, and are harder to be understood by others. This work aims to propose a framework, where the development of methods can be done in a modular manner, creating workflows based on key steps that can be linked together to generate the input classification. For this, a study of the literature was conducted to identify the main processing steps of the methods, seeking to develop a solution that would guarantee flexibility of execution and interoperability between the different processing components. With this, the automatic verification process was described in a limited set of steps that can be performed, creating independent components that implement each of them. The framework makes use of a proposed data traceability ontology to map all generated data during execution under a unified vocabulary, which facilitates communication between these independent components.