OEKG: The Open Event Knowledge Graph

Simon Gottschalk, Endri Kacupaj, Sara Abdollahi, Diego Alves, Gabriel Amaral +9 more
2/28/2023
cs.AI

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Abstract

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.

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Cite this paper

@article{gottschalk2023oekg,
  title  = {OEKG: The Open Event Knowledge Graph},
  author = {Simon Gottschalk and Endri Kacupaj and Sara Abdollahi and Diego Alves and Gabriel Amaral and Elisavet Koutsiana and Tin Kuculo and Daniela Major and Caio Mello and Gullal S. Cheema and Abdul Sittar and Swati and Golsa Tahmasebzadeh and Gaurish Thakkar},
  year   = {2023},
  eprint = {2302.14688},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2302.14688v1}
}

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