Event-QA: A Dataset for Event-Centric Question Answering over Knowledge Graphs

Costa, Tarcísio Souza, Gottschalk, Simon, Demidova, Elena

arXiv.org Artificial Intelligence 

Semantic Question Answering (QA) is the key technology to facilitate intuitive user access to semantic information stored in knowledge graphs. Whereas most of the existing QA systems and datasets focus on entity-centric questions, very little is known about the performance of these systems in the context of events. As new event-centric knowledge graphs emerge, datasets for such questions gain importance. In this paper we present the Event-QA dataset for answering event-centric questions over knowledge graphs. Event-QA contains 1000 semantic queries and the corresponding English, German and Portuguese verbalisations for EventKG - a recently proposed event-centric knowledge graph with over 970 thousand events.

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