Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866913296405233664 |
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| author | Srikanth, Neha Sarkar, Rupak Mane, Heran Aparicio, Elizabeth M. Nguyen, Quynh C. Rudinger, Rachel Boyd-Graber, Jordan |
| author_facet | Srikanth, Neha Sarkar, Rupak Mane, Heran Aparicio, Elizabeth M. Nguyen, Quynh C. Rudinger, Rachel Boyd-Graber, Jordan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_09542 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering Srikanth, Neha Sarkar, Rupak Mane, Heran Aparicio, Elizabeth M. Nguyen, Quynh C. Rudinger, Rachel Boyd-Graber, Jordan Computation and Language 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. |
| title | Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2311.09542 |