Toward a computer study of the reliability of Arabic stories

The Arabic storytelling methodology provides solutions to the problem of information reliability. The reliability of a story depends on the credibility of its narrators. To insure reliability verification, the narrators' names are explicitly cited at the head of the story, which constitute its chain of narrators. Stories were reported from a generation to another to insure the reliable transmission of historical knowledge. We present a set of tools based on the Arabic storytelling methodology. We start by presenting this methodology as a set of principles for information‐reliability assessment. Then, we detail an architecture designed to support the study of the reliability of Arabic stories. Indeed, we developed grammars for parsing Arabic full names and chains of narrators of Arabic stories. After that, an intelligent identity recognizer links names found in chains of narrators to the biographies of the corresponding persons. We model this step as a possibilistic information retrieval task. Finally, chains are analyzed through metadata available in biographies to help the user identify sources of unreliability. We propose to identify the class of reliability of a story with a possibilistic classifier. The achieved results in named entity and identity recognition were satisfactory and confirm to the targets set for the precision, recall, and F‐measure metrics. The developed tools also are reusable components that can be used to study the reliability of other types of Arabic texts.