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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BoolQ is a question answering dataset for yes/no questions containing 15942 examples. These questions are naturally occurring ---they are generated in unprompted and unconstrained settings. Each example is a triplet of (question, passage, answer), with the title of the page as optional additional context. The text-pair classification setup is similar to existing natural language inference tasks.