Semantic role labeling tools for biomedical question answering: a study of selected tools on the BioASQ datasets

Fabian Eckert, Mariana Neves


Abstract
Question answering (QA) systems usually rely on advanced natural language processing components to precisely understand the questions and extract the answers. Semantic role labeling (SRL) is known to boost performance for QA, but its use for biomedical texts has not yet been fully studied. We analyzed the performance of three SRL tools (BioKIT, BIOSMILE and PathLSTM) on 1776 questions from the BioASQ challenge. We compared the systems regarding the coverage of the questions and snippets, as well as based on pre-defined criteria, such as easiness of installation, supported formats and usability. Finally, we integrated two of the tools in a simple QA system to further evaluate their performance over the official BioASQ test sets.
Anthology ID:
W18-5302
Volume:
Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering
Month:
November
Year:
2018
Address:
Brussels, Belgium
Venues:
BioASQ | EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11–21
Language:
URL:
https://www.aclweb.org/anthology/W18-5302
DOI:
10.18653/v1/W18-5302
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/W18-5302.pdf