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