With the growing amount of online data, distinguishing between similar events and news about them poses a significant challenge for both companies and crisis reaction units. To discriminate event instances, we present Eventist, a silver-standard event instance dataset from news in English, containing 23,304 news headlines from 90 countries covering in total 113 storm-related events between 1^st January 2021 and 1^st September 2023. Sampled data is validated by two human raters. Additionally, we propose to adopt a sentence-level event representation for modeling media narrative discourse. Finally, we provide two pairwise comparison benchmarks on event deduplication and event temporal ordering, enabling the practicality of event extraction.