Hyper-parameter value range notes number of BiLSTM layers {2, 3} layer connections {stitch, skip} stitch denotes learnable β parameters, while skip only uses the last BiLSTM layer as classification input subspace constraint weights {0.1, 0.2}  In our experiments, we consider four different non-literal language tasks (Table 3).
we include two metaphor detection tasks, with data being annotated on a token and on a construction level (i.e., grammatical constructions that share one label).