A dataset for trivia question answering, which is a task that requires answering questions about general knowledge and facts. A trivia question answering dataset typically consists of a large number of question-answer pairs, covering various topics and domains, such as history, geography, science, sports, entertainment, etc. The questions are usually authored by trivia enthusiasts or collected from trivia websites, and the answers are often verified by human annotators or evidence documents. A trivia question answering dataset can be used to evaluate the ability of question answering models to understand natural language, retrieve relevant information, and reason with commonsense knowledge

A trivia question answering dataset can be used to test the performance of question answering models on a challenging and realistic task that requires both breadth and depth of knowledge. It can also be used to encourage the development of more robust and generalizable models that can handle diverse and complex questions. Moreover, a trivia question answering dataset can be used to enhance the user experience of search engines, chatbots, voice assistants, and educational applications by providing engaging and informative answers to users’ queries

• Here is an example question from the TriviaQA dataset, which is one of the most popular trivia question answering datasets:
  • What is the name of the largest bone in the human body? A) Humerus – B) Femur – C) Tibia – D) Pelvis
  • The correct answer is B, as the femur is the longest and strongest bone in the human body.

• The original paper by Joshi et al. that introduces the TriviaQA dataset and the adversarial filtering method.
• The Papers With Code website that lists the papers and code related to the TriviaQA dataset and task.
• The GitHub repository by ad-freiburg that contains a collection of large question answering datasets, including trivia question answering datasets.
• The TensorFlow website that provides the documentation for loading and using the TriviaQA dataset
• NQ