From Table 1, we see that the best performances (highest accuracy on Definition and lowest accuracy on Stereotype) are reported by GP (GN-GloVe), which is the application of the proposed method to debias word embeddings learnt by GN-GloVe.
in both SemBias and SemBias-subset, GP (GN-GloVe) statistically significantly outperforms GloVe and Hard-Glove according to Clopper-Pearson confidence intervals (Clopper and Pearson, 1934).