QuAC
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About
QuAC (Question Answering in Context) is a dataset for modeling, understanding, and participating in information seeking dialog. Data instances consist of an interactive dialog between two crowd workers: a student who poses a sequence of freeform questions to learn as much as possible about a hidden Wikipedia text, and a teacher who answers the questions by providing short excerpts (spans) from the text. QuAC introduces challenges not found in existing machine comprehension datasets: its questions are often more open-ended, unanswerable, or only meaningful within the dialog context.
Platform
Features
• models information seeking dialog
• unanswerable questions
• span-based evaluation
• interactive dialog between a student and a teacher
• question answering in context
FAQs
Is QuAC exactly like SQuAD 2.0?
No, QuAC shares many principles with [SQuAD 2.0 ](https://rajpurkar.github.io/SQuAD-explorer/)such as span based evaluation and unanswerable questions (including website design principles! Big thanks for sharing the code!) but incorporates a new dialog component.
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