FEEL: Framework for the integration of Entity Extraction and Linking systems

摘要: Abstract Entity extraction and linking (EEL) is an important task of the Semantic Web that allows to identify real-world objects from text associate them with their respective resources a Knowledge Base. Thus, one purpose EEL extract knowledge text. In recent years, several systems have been proposed for addressing such in domains, languages, bases. this sense, some combine benefits varied kind ensemble system (like Machine Learning) provide better performance extractions than using single system. However, there are no clear indications selection, configuration, result integration setting. This paper proposes framework by providing recommendations selection systems, configuration input parameters, execution final results through filtering strategy measures occurrence entities detects overlapping entities. Based on framework, we implemented existing (through publicly available APIs). The experiments were performed GERBIL framework. Our demonstrate improvement micro/macro- precision recall regarding selected individual over seven datasets.