An alternative way to extend world knowledge is to learn from largescale unlabeled data (Wu, 2003;Yu et al., 2008).
the unsupervised approach accumulates errors caused by automatic annotation processes, such as word segmentation, PoS tagging, syntactic parsing, and semantic role assignment.