Learning Gender-Neutral Word Embeddings
Table 1: Percentage of predictions for each category on gender relational analogy task.
['Dataset', 'Embeddings', 'Definition', 'Stereotype', 'None']
GN-GloVe achieves 97.7% accuracy in identifying gender-definition word pairs as an analogy to “he - she”. In contrast, GloVe and Hard-GloVe makes significantly more mistakes. On the subset, GN-GloVe also achieves significantly better performance than Hard-Glove and GloVe, indicating that it can generalize the gender pairs on the training set to identify other gender-definition word pairs.