We then map these features into a low dimensional space.
we compute an embed-ding of the argument features: , wherev a w ∈ R k is the average of argument word embeddings,v a d ∈ R k is the average embedding of the argument's dependents, andv a l ∈ R k is the average embedding of the corresponding dependency labels.