DRCD: a Chinese Machine Reading Comprehension Dataset

Abstract

In this paper, we introduce DRCD (Delta Reading Comprehension Dataset), an open domain traditional Chinese machine reading comprehension (MRC) dataset. This dataset aimed to be a standard Chinese machine reading comprehension dataset, which can be a source dataset in transfer learning. The dataset contains 10,014 paragraphs from 2,108 Wikipedia articles and 30,000+ questions generated by annotators. We build a baseline model that achieves an F1 score of 89.59%. F1 score of Human performance is 93.30%.

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• Teaching Machines to Read and Comprehend
• The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations
• QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension
• DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

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