Bf3R at SemEval-2018 Task 7: Evaluating Two Relation Extraction Tools for Finding Semantic Relations in Biomedical Abstracts

Mariana Neves, Daniel Butzke, Gilbert Schönfelder, Barbara Grune


Abstract
Automatic extraction of semantic relations from text can support finding relevant information from scientific publications. We describe our participation in Task 7 of SemEval-2018 for which we experimented with two relations extraction tools - jSRE and TEES - for the extraction and classification of six relation types. The results we obtained with TEES were significantly superior than those with jSRE (33.4% vs. 30.09% and 20.3% vs. 16%). Additionally, we utilized the model trained with TEES for extracting semantic relations from biomedical abstracts, for which we present a preliminary evaluation.
Anthology ID:
S18-1130
Volume:
Proceedings of The 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
816–820
Language:
URL:
https://www.aclweb.org/anthology/S18-1130
DOI:
10.18653/v1/S18-1130
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1130.pdf