Ask To The Point: Open-Domain Entity-Centric Question Generation

• URL: http://arxiv.org/abs/2310.14126v1
• Date: Sat, 21 Oct 2023 22:19:19 GMT
• Title: Ask To The Point: Open-Domain Entity-Centric Question Generation
• Authors: Yuxiang Liu, Jie Huang, Kevin Chen-Chuan Chang
• Abstract summary: We introduce a new task called *entity-centric question generation* (ECQG) The task aims to generate questions from an entity perspective. To solve ECQG, we propose a coherent PLM-based framework GenCONE with two novel modules: content focusing and question verification.
• Score: 27.5948850672624
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce a new task called *entity-centric question generation* (ECQG), motivated by real-world applications such as topic-specific learning, assisted reading, and fact-checking. The task aims to generate questions from an entity perspective. To solve ECQG, we propose a coherent PLM-based framework GenCONE with two novel modules: content focusing and question verification. The content focusing module first identifies a focus as "what to ask" to form draft questions, and the question verification module refines the questions afterwards by verifying the answerability. We also construct a large-scale open-domain dataset from SQuAD to support this task. Our extensive experiments demonstrate that GenCONE significantly and consistently outperforms various baselines, and two modules are effective and complementary in generating high-quality questions.

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