From Mirza (2016): "In NLP, the definition of an event can be varied depending on the target application. In topic detection and tracking (Allan, 2002), the term event is used interchangeably with topic, which describes something that happens and is usually used to identify a cluster of documents, e.g., Olympics, wars. On the other hand, information extraction provides finer granularity of event definitions, in which events are entities that happen/occur within the scope of a document."
TODO: From Ponti and Korhonen (2017): "Events are complex entities bridging between semantic meaning and the syntactic form (Croft, 2002)."
- Mirza, P., 2016. Extracting Temporal and Causal Relations between Events. arXiv preprint arXiv:1604.08120.
- Ponti, E. M., & Korhonen, A. (2017). Event-Related Features in Feedforward Neural Networks Contribute to Identifying Causal Relations in Discourse. The 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-Level Semantics (ISDSEM 2017), 25–30.