For all our models, the label sets W 1 = W 2 contain 30,693 lemmas (20,410 nouns, 5,026 verbs, and 5,257 adjectives).
we use the memory-efficient MET(1) algorithm of Kolda and Sun (2008) as implemented in the Matlab Tensor Toolbox.