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'Making the News': Identifying Noteworthy Events in News Articles

机译:“制作新闻”:在新闻文章中识别值得注意的事件

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摘要

Most events described in a news article are background events - only a small number are noteworthy, and a even smaller number serve as the trigger for writing of that article. Although these events are difficult to identify, they are crucial to NLP tasks such as first story detection, document summarization and event coreference, and to many applications of event analysis that depend on event counting and identifying trends. In this work, we introduce the notion of news-peg, a concept borrowed from the political science literature, in an attempt to remedy this problem. A news-peg is an event which prompted the author to write the article, and it serves as a more fine-grained measure of noteworthiness than a summary. We describe a new task of news-peg identification and release an annotated dataset for its evaluation. We formalize an operational definition of a news-peg, on which human anno-tators achieve high inter-annotator agreement (over 80%), and present a rule-based system for this task, which exploits syntactic features derived from established journalistic devices.
机译:新闻文章中描述的大多数事件都是背景事件,只有少数是值得注意的事件,甚至更少的事件是撰写该文章的触发因素。尽管这些事件难以识别,但它们对于NLP任务(例如,第一个故事检测,文档摘要和事件共指)以及依赖于事件计数和识别趋势的事件分析的许多应用至关重要。在这项工作中,我们引入了“新闻钉”的概念,这是从政治学文献中借来的一个概念,旨在解决这个问题。新闻挂钩事件是促使作者撰写文章的事件,与摘要相比,它是更精细的注意程度度量。我们描述新闻钉识别的新任务,并发布一个带注释的数据集以对其进行评估。我们对新闻挂钩的操作定义进行了形式化,人类注释者在该定义上达成了高度的注释者之间的共识(超过80%),并提出了基于规则的系统来执行此任务,该系统利用了来自已建立的新闻手段的句法特征。

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