Question Answering Datasets

Question answering is a natural language processing task that answers questions based on a given context. This is an important task in natural language processing that is used in many applications, such as search, customer support, and chatbots.

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CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge to predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers. The dataset is provided in two major training/validation/testing set splits: "Random split" which is the main evaluation split, and "Question token split", see paper for details.