A unified framework for contextual and factoid question generation

• Main Authors: DONG, Chenhe, SHEN, Ying, LIN, Shiyang, LIN, Zhenzhou, DENG, Yang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Question generation; multi-task learning; knowledge acquisition; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/9085; https://ink.library.smu.edu.sg/context/sis_research/article/10088/viewcontent/10136803.pdf
• Institution: Singapore Management University

Question generation (QG) aims to automatically generate fluent and relevant questions, where the two most mainstream directions are generating questions from unstructured contextual texts (CQG), such as news articles, and generating questions from structured factoid texts (FQG), such as knowledge gr...