Sequence Tagging for Biomedical Extractive Question Answering

by   Wonjin Yoon, et al.

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 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). In real-world use cases, this emphasizes the need for Biomedical EQA models able to handle multiple question types. Based on this preliminary study, we propose a multi-span extraction setting, namely sequence tagging approach for BioEQA, which directly tackles questions with a variable number of phrases as their answer. Our approach can learn to decide the number of answers for a question from training data. Our experimental result on the BioASQ 7b and 8b list-type questions outperformed the best-performing existing models without requiring post-processing steps.


page 1

page 2

page 3

page 4


Pre-trained Language Model for Biomedical Question Answering

The recent success of question answering systems is largely attributed t...

Activity report analysis with automatic single or multispan answer extraction

In the era of loT (Internet of Things) we are surrounded by a plethora o...

ListReader: Extracting List-form Answers for Opinion Questions

Question answering (QA) is a high-level ability of natural language proc...

Weakly-Supervised Open-Retrieval Conversational Question Answering

Recent studies on Question Answering (QA) and Conversational QA (ConvQA)...

Few-Shot Question Answering by Pretraining Span Selection

In a number of question answering (QA) benchmarks, pretrained models hav...

Explanation Container in Case-Based Biomedical Question-Answering

The National Center for Advancing Translational Sciences(NCATS) Biomedic...

Tag and Correct: Question aware Open Information Extraction with Two-stage Decoding

Question Aware Open Information Extraction (Question aware Open IE) take...