On top of the model, a CRF (Lafferty et al., 2001) layer is employed to capture the dependencies among predicted tags.
given an input sequence X and the output of the linear layer Y = {y 1 , ..., y L }, we define the score of a se-quence of predictionsẑ = {ẑ 1 , ...,ẑ L } to be where Aẑ i−1 ,ẑ i is the score of transitioning from tagẑ i−1 to tagẑ i , and y i,ẑ i is the component of y i that corresponds to tagẑ i .