Extracting events from news stories as the aim of several Natural Language Processing (NLP) applications (e.g., question answering, news recommendation, news summarization) is not a trivial task, due to the complexity of natural language and the fact that news reporting is characterized by journalistic style and norms. Those aspects entail scattering an event description over several sentences within one document (or more documents), applying a mechanism of gradual specification of event-related information. This implies a widespread use of co-reference relations among the textual elements, conveying non-linear temporal information. In addition to this, despite the achievement of state-of-the-art results in several tasks, high-quality training datasets for non-English languages are rarely available.