Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering

Neha Srikanth,Rupak Sarkar, Heran Mane, Elizabeth M. Aparicio, Quynh C. Nguyen,Rachel Rudinger,Jordan Boyd-Graber

arxiv(2023)

引用 0|浏览3
暂无评分
摘要
Questions posed by information-seeking users often contain implicit false or potentially harmful assumptions. In a high-risk domain such as maternal and infant health, a question-answering system must recognize these pragmatic constraints and go beyond simply answering user questions, examining them in context to respond helpfully. To achieve this, we study assumptions and implications, or pragmatic inferences, made when mothers ask questions about pregnancy and infant care by collecting a dataset of 2,727 inferences from 500 questions across three diverse sources. We study how health experts naturally address these inferences when writing answers, and illustrate that informing existing QA pipelines with pragmatic inferences produces responses that are more complete, mitigating the propagation of harmful beliefs.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要