Inspired by this, we propose an attentionbased hierarchical context encoder (HiCE), which can leverage both sentence examples and morphological information.
the proposed model adopts multi-head self-attention to integrate information extracted from multiple contexts, and the morphological information can be easily integrated through a character-level CNN encoder.