It challenges a system to predict similarity scores between cross-lingual word pairs with sentential context provided in both languages.
given a dictionary with item pairs from source and target languages (s i , t i ), and matrices S and T that contain the vector representations corresponding to the item pairs in the columns, we follow the standard practice  to find an orthogonal alignment matrix W that minimizes the distance between the transformed matrix W S and T .