Before revision:  We adopt the Bi-LSTM layers and a pre-trained BERT encoder respectively as its encoder module , and obtain promising results in a public English dataset as well as a Chinese one.
After revision:  We adopt the Bi-LSTM layers and a pre-trained BERT encoder respectively as its encoder module , and obtain promising results in public English as well as a Chinese one.