(2017) utilize the entity type embedding directly as local context of the current word, and calculate the attention values between them; others (Liu et al., 2018b(Liu et al., , 2019Nguyen and Grishman, 2018) concatenate the entity type embeddings with the work token embeddings, in order to integrate these two types of features into mixed representations with the help of neural networks.
these existing studies ignore the entity types' sequential features which may benefit the ED task.