We found that (Huang et al., 2013) failed to resolve many unpopular morphs (e.g., "小马 (Little Ma)" is a morph referring to Ma Yingjiu, and it only appeared once in the data), because it heavily relies on aggregating contextual and temporal information from multiple instances of each morph.
our unsupervised resolution approach only leverages the pre-trained word embeddings to capture the semantics of morph mentions and entities.