To see how our approach would perform as the degree of data imbalance varies, we used the same random seed to sample negative instances extracted from the Chinese corpus of ACE 2005 to add to the positive instances with different negative/positive instance ratios of 1:0.5, 1:1, 1:5, 1:10 and 1:15.
we further incorporate the embeddings of character-wise/word-wise BIO tag from the named entity recognition task into character/word embeddings to enrich the input representation.