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arXiv · 1910.06701

NumNet: Machine Reading Comprehension with Numerical Reasoning

Qiu Ran·Yankai Lin·Peng Li·Jie Zhou·Zhiyuan Liu
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Abstract

Numerical reasoning, such as addition, subtraction, sorting and counting is a critical skill in human's reading comprehension, which has not been well considered in existing machine reading comprehension (MRC) systems. To address this issue, we propose a numerical MRC model named as NumNet, which utilizes a numerically-aware graph neural network to consider the comparing information and performs numerical reasoning over numbers in the question and passage. Our system achieves an EM-score of 64.56% on the DROP dataset, outperforming all existing machine reading comprehension models by considering the numerical relations among numbers.

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Qiu Ran, Yankai Lin, Peng Li, Jie Zhou, Zhiyuan Liu. 2019-10-15. NumNet: Machine Reading Comprehension with Numerical Reasoning. https://arxiv.org/abs/1910.06701

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