To further strengthen their relations, the labels of the target word are also used to predict the target word.
given a sequence of T words (W 1 ,..,W t ,...,W T ) and their annotations ((A 1,1 ,...,A 1,M 1 ),...,(A T,1 ,...,A T,M T )), the objec- tive of the WAE model is to maximize the average log probability shown in Equation 1, where C is the size of the context window, W t is the target word, W t+j is a context word, M t is number of annotations W t has and A t,k is the k-th annotation Label-aware Negative Sampling: Negative sampling (Mikolov et al., 2013) was introduced as an approximation method in word2vec to improve the efficiency of model training.