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    <abstract>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.</abstract>
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%0 Conference Proceedings
%T Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering
%A Srikanth, Neha
%A Sarkar, Rupak
%A Mane, Heran
%A Aparicio, Elizabeth
%A Nguyen, Quynh
%A Rudinger, Rachel
%A Boyd-Graber, Jordan
%Y Duh, Kevin
%Y Gomez, Helena
%Y Bethard, Steven
%S Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F srikanth-etal-2024-pregnant
%X 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.
%U https://aclanthology.org/2024.naacl-long.403
%P 7246-7261

Markdown (Informal)

[Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering](https://aclanthology.org/2024.naacl-long.403) (Srikanth et al., NAACL 2024)

• Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering (Srikanth et al., NAACL 2024)

ACL

• Neha Srikanth, Rupak Sarkar, Heran Mane, Elizabeth Aparicio, Quynh Nguyen, Rachel Rudinger, and Jordan Boyd-Graber. 2024. Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 7246–7261, Mexico City, Mexico. Association for Computational Linguistics.