English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

One of the key requirements to facilitate the semantic analytics ofinformation regarding contemporary and historical events on the Web, in thenews and in social media is the availability of reference knowledgerepositories containing comprehensive representations of events, entities andtemporal relations. Existing knowledge graphs, with popular examples includingDBpedia, YAGO and Wikidata, focus mostly on entity-centric information and areinsufficient in terms of their coverage and completeness with respect to eventsand temporal relations. In this article we address this limitation, formalisethe concept of a temporal knowledge graph and present its instantiation -EventKG. EventKG is a multilingual event-centric temporal knowledge graph thatincorporates over 690 thousand events and over 2.3 million temporal relationsobtained from several large-scale knowledge graphs and semi-structured sourcesand makes them available through a canonical RDF representation. Whereaspopular entities often possess hundreds of relations within a temporalknowledge graph such as EventKG, generating a concise overview of the mostimportant temporal relations for a given entity is a challenging task. In thisarticle we demonstrate an application of EventKG to biographical timelinegeneration, where we adopt a distant supervision method to identify relationsmost relevant for an entity biography. Our evaluation results provide insightson the characteristics of EventKG and demonstrate the effectiveness of theproposed biographical timeline generation method.

EventKG - the Hub of Event Knowledge on the Web - and Biographical Timeline Generation