2021
DOI: 10.48550/arxiv.2104.07535
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Sequence Tagging for Biomedical Extractive Question Answering

Wonjin Yoon,
Richard Jackson,
Jaewoo Kang
et al.

Abstract: Current studies in extractive question answering (EQA) have modeled 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 single-span extraction setting with post-processing steps. In this paper, we investigate the difference of th… Show more

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Cited by 2 publications
(3 citation statements)
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“…PubMedBERT [66], BioMegatron [215], Yoon et al [284], Jeong et al [89], Chakraborty et al [30], Kamath et al [100], Du et al [52], Yoon et al [283], Zhou et al [300], Akdemir et al [5], He et al [78], Amherst et al [200], Kommaraju et al [112], for COVID-19 [55,120,170,201], Soni et al [222], Mairittha et al [147]. Dialogue Systems Zeng at al.…”
Section: Question Answeringmentioning
confidence: 99%
See 1 more Smart Citation
“…PubMedBERT [66], BioMegatron [215], Yoon et al [284], Jeong et al [89], Chakraborty et al [30], Kamath et al [100], Du et al [52], Yoon et al [283], Zhou et al [300], Akdemir et al [5], He et al [78], Amherst et al [200], Kommaraju et al [112], for COVID-19 [55,120,170,201], Soni et al [222], Mairittha et al [147]. Dialogue Systems Zeng at al.…”
Section: Question Answeringmentioning
confidence: 99%
“…However, these models can only extract a single span of passage as the answer and can not detect multiple spans of the passage when there are multiple answers for the question. To solve the problem, Yoon et al [283] reformulated the task as the sequence tagging problem to detect multiple entity spans simultaneously. They used the BioBERT as the encoder and concatenated the Sequence Tagging Layer including the linear layer, Bi-LSTM and Bi-LSTM+CRF to predicting the tag of each token.…”
Section: Question Answeringmentioning
confidence: 99%
“…Their systems are based on the transformers models and follow either a model-centric or a data-centric approach. The former, which is based on the sequence tagging approach [45], is used for list questions while the latter, which relies on the characteristics of the training datasets and therefore data cleaning and sampling are important aspects of its architecture, is used for factoid questions. For yes/no questions, they utilized the BioBERT-large model, as a replacement of the previously used BioBERT-BASE model.…”
Section: Systemsmentioning
confidence: 99%