تقرير
Sequence tagging for biomedical extractive question answering
| العنوان: | Sequence tagging for biomedical extractive question answering |
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| المؤلفون: | Yoon, Wonjin, Jackson, Richard, Lagerberg, Aron, Kang, Jaewoo |
| المصدر: | Bioinformatics, 2022, 1-8 |
| سنة النشر: | 2021 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | Current studies in extractive question answering (EQA) have modeled the single-span extraction setting, where a single answer span is a label to predict for a given question-passage pair. This setting is natural for general domain EQA as the majority of the questions in the general domain can be answered with a single span. Following general domain EQA models, current biomedical EQA (BioEQA) models utilize the single-span extraction setting with post-processing steps. In this article, we investigate the question distribution across the general and biomedical domains and discover biomedical questions are more likely to require list-type answers (multiple answers) than factoid-type answers (single answer). This necessitates the models capable of producing multiple answers for a question. Based on this preliminary study, we propose a sequence tagging approach for BioEQA, which is a multi-span extraction setting. Our approach directly tackles questions with a variable number of phrases as their answer and can learn to decide the number of answers for a question from training data. Our experimental results on the BioASQ 7b and 8b list-type questions outperformed the best-performing existing models without requiring post-processing steps. Source codes and resources are freely available for download at https://github.com/dmis-lab/SeqTagQA Comment: Published as "advanced access". Bioinformatics (2022). Supplementary data are available at Bioinformatics online |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1093/bioinformatics/btac397 |
| URL الوصول: | http://arxiv.org/abs/2104.07535 |
| رقم الأكسشن: | edsarx.2104.07535 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1093/bioinformatics/btac397 |
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