Asking Questions Like Educational Experts: Automatically Generating Question-Answer Pairs on Real-World Examination Data

• URL: http://arxiv.org/abs/2109.05179v1
• Date: Sat, 11 Sep 2021 04:10:57 GMT
• Title: Asking Questions Like Educational Experts: Automatically Generating Question-Answer Pairs on Real-World Examination Data
• Authors: Fanyi Qu, Xin Jia, Yunfang Wu
• Abstract summary: This paper addresses the question-answer pair generation task on the real-world examination data, and proposes a new unified framework on RACE. We propose a multi-agent communication model to generate and optimize the question and keyphrases iteratively, and then apply the generated question and keyphrases to guide the generation of answers. Experimental results show that our model makes great breakthroughs in the question-answer pair generation task.
• Score: 10.353009081072992
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Generating high quality question-answer pairs is a hard but meaningful task. Although previous works have achieved great results on answer-aware question generation, it is difficult to apply them into practical application in the education field. This paper for the first time addresses the question-answer pair generation task on the real-world examination data, and proposes a new unified framework on RACE. To capture the important information of the input passage we first automatically generate(rather than extracting) keyphrases, thus this task is reduced to keyphrase-question-answer triplet joint generation. Accordingly, we propose a multi-agent communication model to generate and optimize the question and keyphrases iteratively, and then apply the generated question and keyphrases to guide the generation of answers. To establish a solid benchmark, we build our model on the strong generative pre-training model. Experimental results show that our model makes great breakthroughs in the question-answer pair generation task. Moreover, we make a comprehensive analysis on our model, suggesting new directions for this challenging task.

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