For our baseline supertagging model we use the state-of-the-art model that currently has the highest accuracy on the Penn treebank dataset <cite>(Kasai et al., 2018)</cite> . For the supertagging model the main contribution of<cite> Kasai et al. (2018)</cite> was two-fold: the first was to add a character CNN for modeling word embeddings using subword features, and the second was to add highway connections to add more layers to a standard bidirectional LSTM.