Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology
Table 1: Morphological reinflection accuracies.
['Language French', 'Accuracy 93.17', 'Language Italian', 'Accuracy 98.29']
Once the new tags have been inferred, the final step is to reinflect the lemmata to their new forms. This task has received considerable attention from the NLP community . We use the inflection model of \newciteD18-1473. This model conditions on the lemma x and morpho-syntactic tag m to form a distribution over possible inflections. For example, given experto and [\textsca;\textscfem;\textscpl], the trained inflection model will assign a high probability to expertas.