Mohammed Aldawsari · COLING 2020
270 - Distinguishing Between Foreground and Background Events in News
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, summarization, 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 combinations). We achieve good performance (0.73 F_1 for background vs. foreground and temporal position, and 0.79 F_1 for background vs. foreground only) on a dataset of news articles by leveraging discourse information in a featurized model.