Fernàndez D, Bou E, Giró-i-Nieto X. VLX-Stories: building an online Event Knowledge Base with Emerging Entity detection. In The Semantic Web – ISWC 2019. Auckland, New Zealand: Springer, Cham; 2019. pp. 382-399.  (1.42 MB)


We present an online multilingual system for event detection and comprehension from media feeds. The system retrieves information from news sites and social networks, aggregates them into events (event detection), and summarizes them by extracting semantic labels of its most relevant entities (event representation) in order to answer the journalism W's: who, what, when and where. The generated events populate VLX-Stories -an event Knowledge Base (KB)- transforming unstructured text data to a structured knowledge base representation. Our system exploits an external entity Knowledge Base (VLX-KG) to help populate VLX-Stories. At the same time, this external knowledge base can also be extended with a Dynamic Entity Linking (DEL) module, which detects Emerging Entities (EE) on unstructured data and adds them to VLX-KG. The system is currently used in production, detecting over 6000 monthly events from over 3500 news feeds from seven different countries and in three different languages.