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.
@article{arxiv.2310.14126,
title = {Ask To The Point: Open-Domain Entity-Centric Question Generation},
author = {Yuxiang Liu and Jie Huang and Kevin Chen-Chuan Chang},
journal= {arXiv preprint arXiv:2310.14126},
year = {2023}
}
Comments
Accepted to the Findings of EMNLP 2023. Camera-ready version