Distinguishing Between Foreground and Background Events in News
Distinguishing Between Foreground and Background Events in News
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DOI：
10.18653/v1/2020.coling-main.453
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发表时间：
2020-12
期刊：
影响因子：
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通讯作者：
Mohammed Aldawsari;Adrián Pérez;Deya Banisakher;Mark A. Finlayson
中科院分区：
文献类型：
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作者：
Mohammed Aldawsari;Adrián Pérez;Deya Banisakher;Mark A. Finlayson
确定新闻文章中的事件是前景事件还是背景事件在许多自然语言处理任务中将是有用的，例如，时间关系提取、摘要或故事情节生成。我们介绍了区分新闻文章中的前景和背景事件的任务，以及确定背景事件相对于前景时期（过去，现在，未来及其组合）的一般时间位置。我们实现了良好的性能（0.73 F1的背景与前景和时间位置，和0.79 F1的背景与前景只）的新闻文章的数据集，利用话语信息的特征化模型。我们为其他研究人员发布我们的实现和注释数据
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 F1 for background vs. foreground and temporal position, and 0.79 F1 for background vs. foreground only) on a dataset of news articles by leveraging discourse information in a featurized model. We release our implementation and annotated data for other researchers