Although this approach has achieved the top performance (Hong et al., 2011;<cite> Li et al., 2013b)</cite> , it suffers from at least two issues: (i) The choice of features is a manual process and requires linguistic intuition as well as domain expertise, implying additional studies for new application domains and limiting the capacity to quickly adapt to these new domains. (ii) The supervised NLP toolkits and resources for feature extraction might involve errors (either due to the imperfect nature or the performance loss of the toolkits on new domains (Blitzer et al., 2006; Daumé III, 2007; McClosky et al., 2010) ), probably propagated to the final event detector.