EventKG – the hub of event knowledge on the web – and biographical timeline generation

Abstract

One of the key requirements to facilitate the 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, entities 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. In this article we address this limitation, formalise the concept of a temporal knowledge graph and present its instantiation -EventKG. EventKG is a multilingual event-centric temporal knowledge graph that incorporates over 690 thousand events and over 2.3 million temporal relations obtained from several large-scale knowledge graphs and semi-structured sources and makes them available through a canonical RDF representation. Whereas popular entities often possess hundreds of relations within a temporal knowledge graph such as EventKG, generating a concise overview of the most important temporal relations for a given entity is a challenging task. In this article we demonstrate an application of EventKG to biographical timeline generation, where we adopt a distant supervision method to identify relations most relevant for an entity biography. Our evaluation results provide insights on the characteristics of EventKG and demonstrate the effectiveness of the proposed biographical timeline generation method.

Entity summarization with high readability and low redundancy

“…各数据集上的结果见表 4. [15,16] 和时间轴 [17] 等, 其研究对象为特定类型的知识图谱实体. 面向特定任务的 实体摘要, 如用于共指消解的实体摘要方法 C3D+P [5] , 用于实体链接场景的 COMB [4] 等, 其生成的 摘要特定于要辅助用户完成的下游任务.…”

HapPenIng: Happen, Predict, Infer—Event Series Completion in a Knowledge Graph

“…There has been research on several exemplary aspects of knowledge graph completeness, for example on the incompleteness of Wikidata [1,2] and the relation between obligatory attributes and missing attribute values [13]. In our previous work, we considered the problem of integration and fusion of event-centric information spread across different knowledge graphs and created the EventKG knowledge graph that integrates such information [8,10]. [28] addressed the inference of missing categorical information in event descriptions in Web markup.…”

“…Popular knowledge graphs (KGs) such as Wikidata [29], DBpedia [14] and EventKG [8,10] cover event series only to a limited extent. This is due to multiple reasons: First, entity-centric knowledge graphs such as Wikidata and DBpedia do not sufficiently cover events and their spatio-temporal relations [6].…”

Data4UrbanMobility: Towards Holistic Data Analytics for Mobility Applications in Urban Regions

“…Furthermore, we consider event-centric focused crawls from the Web [7] and Web archives [8], [9], as well as Twitter data regarding events and traffic. Another source of event-centric information is the recently proposed EventKG knowledge graph [10,11]. Finally, this information is complemented with geographic data (e.g.…”