Before revision:  In this paper, we propose a novel framework named DKPLM to dynamically select  and embed knowledge context according to textual context for PLMs, which can avoid the effect of redundant and ambiguous knowledge in KGs that cannot match the input text.
After revision:  In this paper, we propose a novel framework named Coke to dynamically select and embed knowledge context according to textual context for PLMs, which can avoid the effect of redundant and ambiguous knowledge in KGs that cannot match the input text.