Machine Translation (MT) enables people to connect with others and engage with content across language barriers. Grammatical gender presents a difficult challenge for these systems, as some languages require specificity for terms that can be ambiguous or neutral in other languages. For example, when translating the English word “nurse” into Spanish, one must decide whether the feminine “enfermera” or the masculine “enfermero” is appropriate. However, particularly when contextual clues are absent, such as in translating a single sentence, a model cannot determine which would be correct. This…
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