Omkar2118/datasets huggingface dataset:
BoolQ
Full name: Boolean Questions

**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.

Questions are gathered from anonymized, aggregated queries to the Google search engine. Queries that are likely to be yes/no questions are heuristically identified and questions are only kept if a Wikipedia page is returned as one of the first five results, in which case the question and Wikipedia page are given to a human annotator for further processing. Annotators label question/article pairs in a three-step process. First, they decide if the question is good, meaning it is comprehensible, unambiguous, and requesting factual information. This judgment is made before the annotator sees the Wikipedia page. Next, for good questions, annotators find a passage within the document that contains enough information to answer the question. Annotators can mark questions as “not answerable” if the Wikipedia article does not contain the requested information. Finally, annotators mark whether the question’s answer is “yes” or “no”. Only questions that were marked as having a yes/no answer are used, and each question is paired with the selected passage instead of the entire document.

Source: [https://github.com/google-research-datasets/boolean-questions](https://github.com/google-research-datasets/boolean-questions)
Image Source: [BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions](https://paperswithcode.com/paper/boolq-exploring-the-surprising-difficulty-of/)

Introducing paper: BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions