U-Net: Machine Reading Comprehension with Unanswerable Questions

Understand

Machine reading comprehension with unanswerable questions is a new challenging task for natural language processing.

• A key subtask is to reliably predict whether the question is unanswerable.
• In this paper, we propose a unified model, called U-Net, with three important components: answer pointer, no-answer pointer, and answer verifier.
• We introduce a universal node and thus process the question and its context passage as a single contiguous sequence of tokens.