EventKG: A Multilingual Event-Centric Temporal Knowledge Graph

TL;DR

EventKG is a comprehensive multilingual knowledge graph focusing on events and temporal relations, filling gaps left by existing entity-centric graphs like DBpedia and Wikidata.

Contribution

It introduces a large-scale, multilingual event-centric temporal knowledge graph with over 690,000 events and 2.3 million temporal relations, integrating multiple sources.

Findings

Provides extensive coverage of events and temporal relations.

Enables improved semantic analytics of historical and contemporary events.

Offers a canonical, accessible representation of event data.

Abstract

One of the key requirements to facilitate semantic analytics of information regarding contemporary and historical events on the Web, in the news and in social media is the availability of reference knowledge repositories containing comprehensive representations of events and temporal relations. Existing knowledge graphs, with popular examples including DBpedia, YAGO and Wikidata, focus mostly on entity-centric information and are insufficient in terms of their coverage and completeness with respect to events and temporal relations. EventKG presented in this paper is a multilingual event-centric temporal knowledge graph that addresses this gap. EventKG incorporates over 690 thousand contemporary and historical events and over 2.3 million temporal relations extracted from several large-scale knowledge graphs and semi-structured sources and makes them available through a canonical representation.