Answering Chinese Elementary School Social Study Multiple Choice Questions

TL;DR

This paper introduces a new framework combining BERT with additional modules to improve performance on Chinese elementary school social study multiple choice questions, especially for question types BERT struggles with.

Contribution

It proposes a novel cascading framework with a Pre-Processor and Answer-Selector modules to enhance BERT's ability on specific question types.

Findings

Improved accuracy over baseline BERT models

Effective handling of negation and all-of-the-above questions

Demonstrated feasibility of supplementing BERT with additional modules

Abstract

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.