데이터셋 탐색

Question Answering in Context is a large-scale dataset that consists of around 14K crowdsourced Question Answering dialogs with 98K question-answer pairs in total. Data instances consist of an interactive dialog between two crowd workers: (1) a student who poses a sequence of freeform questions to learn as much as possible about a hidden Wikipedia text, and (2) a teacher who answers the questions by providing short excerpts (spans) from the text. Source: https://paperswithcode.com/paper/quac-question-answering-in-context-1/ Image Source: https://paperswithcode.com/paper/quac-question-answering-in-context-1/

Hyperquack v.2 response data which contains structured data records in JSON. Censored Planet at the University of Michigan provides this data, which are records of internet censorship test requests using the Echo protocol, and notes: > The raw data posted here needs to be processed to avoid false inferences. Please use our analysis pipeline to process the data before using it. Censored Planet detects network interference of websites using remote measurements to infrastructural vantage points within networks (eg. institutions). Note that this raw data cannot determine the entity responsible for the blocking or the intent behind it. Please exercise caution when using the data