UniMa at SemEval-2018 Task 7: Semantic Relation Extraction and Classification from Scientific Publications

Thorsten Keiper, Zhonghao Lyu, Sara Pooladzadeh, Yuan Xu, Jingyi Zhang, Anne Lauscher, Simone Paolo Ponzetto


Abstract
Large repositories of scientific literature call for the development of robust methods to extract information from scholarly papers. This problem is addressed by the SemEval 2018 Task 7 on extracting and classifying relations found within scientific publications. In this paper, we present a feature-based and a deep learning-based approach to the task and discuss the results of the system runs that we submitted for evaluation.
Anthology ID:
S18-1132
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:
826–830
Language:
URL:
https://www.aclweb.org/anthology/S18-1132
DOI:
10.18653/v1/S18-1132
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1132.pdf