Answering Chinese Elementary School Social Study Multiple Choice Questions
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Abstract (arXiv)
We present a novel approach to answer the Chinese elementary school Social Study Multiple Choice questions. Although BERT has demonstrated excellent performance on Reading Comprehension tasks, it is found not good at handling some specific types of questions, such as Negation, All-of-the-above, and None-of-the-above. We thus propose a novel framework to cascade BERT with a Pre-Processor and an Answer-Selector modules to tackle the above challenges. Experimental results show the proposed approach effectively improves the performance of BERT, and thus demonstrate the feasibility of supplementing BERT with additional modules.
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References · 10
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- 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,148
- 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,811
- 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
- 2015A large annotated corpus for learning natural language inferencecited by 1,847
- 2017RACE: Large-scale ReAding Comprehension Dataset From Examinationscited by 861
- 2016A Decomposable Attention Model for Natural Language Inferencecited by 215
- 2016Enhanced LSTM for Natural Language Inferencecited by 200
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