Event Linking: Grounding Event Mentions to Wikipedia

• URL: http://arxiv.org/abs/2112.07888v1
• Date: Wed, 15 Dec 2021 05:06:18 GMT
• Title: Event Linking: Grounding Event Mentions to Wikipedia
• Authors: Xiaodong Yu, Wenpeng Yin, Nitish Gupta, Dan Roth
• Abstract summary: This work defines Event Linking, a new natural language understanding task at the event level. Event linking tries to link an event mention, appearing in a news article for example, to the most appropriate Wikipedia page.
• Score: 63.087102209379864
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Comprehending an article requires understanding its constituent events. However, the context where an event is mentioned often lacks the details of this event. Then, where can we obtain more knowledge of this particular event in addition to its context? This work defines Event Linking, a new natural language understanding task at the event level. Event linking tries to link an event mention, appearing in a news article for example, to the most appropriate Wikipedia page. This page is expected to provide rich knowledge about what the event refers to. To standardize the research of this new problem, we contribute in three-fold. First, this is the first work in the community that formally defines event linking task. Second, we collect a dataset for this new task. In specific, we first gather training set automatically from Wikipedia, then create two evaluation sets: one from the Wikipedia domain as well, reporting the in-domain performance; the other from the real-world news domain, testing the out-of-domain performance. Third, we propose EveLINK, the first-ever Event Linking approach. Overall, event linking is a considerably challenging task requiring more effort from the community. Data and code are available here: https://github.com/CogComp/event-linking.

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