There have been various works trying to integrate world knowledge into coreference resolution. Ng (2007) added several new features to a coreference resolution system based on machine-learning, e.g. a feature for the semantic similarity of mentions and a feature based on patterns extracted from the training data. Others used knowledge that was extracted from knowledge bases like YAGO (Suchanek et al., 2007), among them Bryl et al. (2010), who model synonyms and mention types using logical constraints in a Markov Logic Network (Richardson and Domingos, 2006), and Rahman and Ng (2011), who extract relation triples between two mentions and convert them into features for their algorithm.