Both evaluations confirm the superiority of our model, where the SP information is effectively preserved and the words' overall semantics are enhanced.
further analysis also indicates that our MWE embeddings are more powerful than all existing embedding methods in SP acquisition with around 1/20 in their size comparing to previous embeddings (Levy and Goldberg, 2014).