In recent years, several biomedical event extraction (EE) systems have been developed. However, the nature of the annotated training corpora, as well as the training process itself, can limit the performance levels of the trained EE systems. In particular, most event-annotated corpora do not deal adequately with coreference. This impacts on the trained systems ability to recognize biomedical entities, thus affecting their performance in extracting events accurately. Additionally, the fact that most EE systems are trained on a single annotated corpus further restricts their coverage.