HapPenIng: Event Series Completion

Event series, such as the Wimbledon Championships and the US presidential elections, represent important happenings in key societal areas including sports, culture and politics. However, semantic reference sources, such as Wikidata and DBpedia knowledge graphs, provide only an incomplete event series representation.
We have targeted the problem of event series completion in a knowledge graph. We addressed two tasks:

1) prediction of sub-event relations, and
2) inference of real-world events that happened as a part of event series and are missing in the knowledge graph.

Data

Evaluation datasets and all other derived datasets are available here.

Cite as

@inproceedings{gottschalk2019happening,
   title={HapPenIng: Happen, Predict, Infer — Event Series Completion in a Knowledge Graph},
   author={Gottschalk, Simon and Demidova, Elena},
   year={2019},
   organization={Springer},
   booktitle={Proceedings of the International Semantic Web Conference (ISWC 2019)}
}