Generating and Ranking Distractors for Multiple-Choice Questions in Portuguese

natural language processing

In the process of multiple-choice question generation, different methods are often considered for distractor acquisition, as an attempt to cover as many questions as possible. Some, however, result in many candidate distractors of variable quality, while only three or four are necessary. We implement some distractor generation methods for Portuguese and propose their combination and ranking with language models. Experimentation results confirm that this increases both coverage and suitability of the selected distractors.