Abstract
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, DBpedia and EventKG knowledge graphs, provide only an incomplete event series representation. In this paper we target the problem of event series completion in a knowledge graph. We address 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. To address these problems, our proposed supervised HapPenIng approach leverages structural features of event series. HapPenIng does not require any external knowledge - the characteristics making it unique in the context of event inference. Our experimental evaluation demonstrates that HapPenIng outperforms the baselines by 44 and 52% points in terms of precision for the sub-event prediction and the inference tasks, correspondingly.
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For example, the event series “TED talk”, whose set of edition template labels (e.g. “Avi Reichental: What’s next in 3D printing” and “Amanda Palmer: The art of asking”) has a high Gini impurity, is not included in the set of event series.
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Existing benchmark datasets do not contain a sufficient amount of sub-event relations. For example, FB15K [3] only contains 224 triples containing one of the Freebase predicates /time/event/includes_event, /time/event/included_in_event or /time/event/instance_of_recurring_event.
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Acknowledgements
This work was partially funded by the EU Horizon 2020 under MSCA-ITN-2018 “Cleopatra” (812997), and the Federal Ministry of Education and Research, Germany (BMBF) under “Simple-ML” (01IS18054).
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Gottschalk, S., Demidova, E. (2019). HapPenIng: Happen, Predict, Infer—Event Series Completion in a Knowledge Graph. In: Ghidini, C., et al. The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science(), vol 11778. Springer, Cham. https://doi.org/10.1007/978-3-030-30793-6_12
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