Distinguishing Between Foreground and Background Events in News

Mark Finlayson

Abstract:

Determining whether an event in a news article is a foreground or background event would be
useful in many natural language processing tasks, for example, temporal relation extraction, sum-
marization, or storyline generation. We introduce the task of distinguishing between foreground
and background events in news articles as well as identifying the general temporal position of
background events relative to the foreground period (past, present, future, and their combina-
tions). We achieve good performance (0.73 F1 for background vs. foreground and temporal
position, and 0.79 F1 for background vs. foreground only) on a dataset of news articles by lever-
aging discourse information in a featurized model. We release our implementation and annotated
data for other researchers