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Event coreference models cluster event mentions pertaining to the samereal-world event. Recent models rely on contextualized representations torecognize coreference among lexically or contextually similar mentions.However, models typically fail to leverage commonsense inferences, which isparticularly limiting for resolving lexically-divergent mentions. We propose amodel that extends event mentions with temporal commonsense inferences. Given acomplex sentence with multiple events, e.g., "The man killed his wife and gotarrested", with the target event "arrested", our model generates plausibleevents that happen before the target event - such as "the police arrived", andafter it, such as "he was sentenced". We show that incorporating suchinferences into an existing event coreference model improves its performance,and we analyze the coreferences in which such temporal knowledge is required.

What happens before and after: Multi-Event Commonsense in Event Coreference Resolution