Before revision:  We show that our approach substantially outperforms baselines and other alternative approaches given the same amount of data, and, through detailed analysis, we argue that data augmentation with the pseudo data from unsupervised machine translation is especially effective for BWEs because (1) the pseudo data makes the source and target corpora (partially) parallel;
After revision:  We show that our approach substantially outperforms baselines and other alternative approaches given the same amount of data, and, through detailed analysis, we argue that data augmentation with the pseudo data from unsupervised machine translation is especially effective for mapping-based CLWEs because (1) the pseudo data makes the source and target corpora (partially) parallel;