Discourse as a Function of Event: Profiling Discourse Structure in News Articles around the Main Event
Prafulla Kumar Choubey, Aaron Lee, Ruihong Huang, Lu Wang
Abstract
Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event. To enable computational modeling of news structures, we apply an existing theory of functional discourse structure for news articles that revolves around the main event and create a human-annotated corpus of 802 documents spanning over four domains and three media sources. Next, we propose several documentlevel neural-network models to automatically construct news content structures. Finally, we demonstrate that incorporating system predicted news structures yields new state-of-theart performance for event coreference resolution. The news documents we annotated are openly available and the annotations are publicly released for future research 1 .