UNCC QA: Biomedical Question Answering system

Abhishek Bhandwaldar, Wlodek Zadrozny


Abstract
In this paper, we detail our submission to the BioASQ competition’s Biomedical Semantic Question and Answering task. Our system uses extractive summarization techniques to generate answers and has scored highest ROUGE-2 and Rogue-SU4 in all test batch sets. Our contributions are named-entity based method for answering factoid and list questions, and an extractive summarization techniques for building paragraph-sized summaries, based on lexical chains. Our system got highest ROUGE-2 and ROUGE-SU4 scores for ideal-type answers in all test batch sets. We also discuss the limitations of the described system, such lack of the evaluation on other criteria (e.g. manual). Also, for factoid- and list -type question our system got low accuracy (which suggests that our algorithm needs to improve in the ranking of entities).
Anthology ID:
W18-5308
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
Editors:
Ioannis A. Kakadiaris, George Paliouras, Anastasia Krithara
Venue:
BioASQ
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
66–71
Language:
URL:
https://aclanthology.org/W18-5308
DOI:
10.18653/v1/W18-5308
Bibkey:
Cite (ACL):
Abhishek Bhandwaldar and Wlodek Zadrozny. 2018. UNCC QA: Biomedical Question Answering system. In Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering, pages 66–71, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
UNCC QA: Biomedical Question Answering system (Bhandwaldar & Zadrozny, BioASQ 2018)
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PDF:
https://aclanthology.org/W18-5308.pdf