OEKG: The Open Event Knowledge Graph
This work addresses the need for cross-lingual event analytics for researchers and applications, but it is incremental as it builds on existing knowledge graphs like EventKG.
The authors tackled the problem of accessing and understanding global events by creating the Open Event Knowledge Graph (OEKG), a multilingual, event-centric, temporal knowledge graph that integrates seven datasets from multiple domains, resulting in a publicly available resource with query endpoint.
Accessing and understanding contemporary and historical events of global impact such as the US elections and the Olympic Games is a major prerequisite for cross-lingual event analytics that investigate event causes, perception and consequences across country borders. In this paper, we present the Open Event Knowledge Graph (OEKG), a multilingual, event-centric, temporal knowledge graph composed of seven different data sets from multiple application domains, including question answering, entity recommendation and named entity recognition. These data sets are all integrated through an easy-to-use and robust pipeline and by linking to the event-centric knowledge graph EventKG. We describe their common schema and demonstrate the use of the OEKG at the example of three use cases: type-specific image retrieval, hybrid question answering over knowledge graphs and news articles, as well as language-specific event recommendation. The OEKG and its query endpoint are publicly available.