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Event extraction from news articles is a commonly required prerequisite forvarious tasks, such as article summarization, article clustering, and newsaggregation. Due to the lack of universally applicable and publicly availablemethods tailored to news datasets, many researchers redundantly implement eventextraction methods for their own projects. The journalistic 5W1H questions arecapable of describing the main event of an article, i.e., by answering who didwhat, when, where, why, and how. We provide an in-depth description of animproved version of Giveme5W1H, a system that uses syntactic anddomain-specific rules to automatically extract the relevant phrases fromEnglish news articles to provide answers to these 5W1H questions. Given theanswers to these questions, the system determines an article's main event. Inan expert evaluation with three assessors and 120 articles, we determined anoverall precision of p=0.73, and p=0.82 for answering the first four Wquestions, which alone can sufficiently summarize the main event reported on ina news article. We recently made our system publicly available, and it remainsthe only universal open-source 5W1H extractor capable of being applied to awide range of use cases in news analysis.

Giveme5W1H: A Universal System for Extracting Main Events from News Articles