Toward Real Event Detection
Published: 2015 Mai
Buchtitel: Proceedings of the 4th International Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web (DeRiVE 2015)
Referierte VeröffentlichungNote: https://dblp.org/rec/bibtex/conf/esws/FarberR15
News agencies and other news providers or consumers are confronted with the task of extracting events from news articles. This is done i) either to monitor and, hence, to be informed about events of specific kinds over time and/or ii) to react to events immediately. In the past, several promising approaches to extracting events from text have been proposed. Besides purely statistically-based approaches there are methods to represent events in a semantically-structured form, such as graphs containing actions (predicates), participants (entities), etc. However, it turns out to be very difficult to automatically determinewhether an event is real or not. In this paper, we give an overview of approaches which proposed solutions for this research problem. We show that there is no gold standard dataset where real events are annotated in text documents in a fine-grained, semantically-enriched way. We present a methodology of creating such a dataset with the help of crowdsourcing and present preliminary results.
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