An Interactive Tool to Bootstrap Semantic Table Interpretation

Abstract

Since it is widely conveyed on the Web, tabular data is mostly organized in a table structure. Indeed, this data format is widely used in multiple scenarios on the web and even within data storage entities. In addition, tabular data is a source of information that deserves to be interpreted and exploited. In this framework, efforts to extract meaningful information from tabular data based on semantic approaches, such as an ontology or a knowledge graph, are commonly referred to as Semantic Table Interpretation (STI). In this paper, we present an interactive tool that deploys a mapping approach to overcome possible semantic gaps in tabular data against a Knowledge Graph. Indeed, the ultimate goal of this tool is to provide an application and adaptable framework that combines search and filtering services associated with text preprocessing techniques. The experimental evaluation was conducted under the SemTab challenge and yielded encouraging and promising results regarding its performance and rankings.