GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification

Sean MacAvaney, Luca Soldaini, Arman Cohan, Nazli Goharian


Abstract
SemEval 2018 Task 7 focuses on relation extraction and classification in scientific literature. In this work, we present our tree-based LSTM network for this shared task. Our approach placed 9th (of 28) for subtask 1.1 (relation classification), and 5th (of 20) for subtask 1.2 (relation classification with noisy entities). We also provide an ablation study of features included as input to the network.
Anthology ID:
S18-1133
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
831–835
Language:
URL:
https://aclanthology.org/S18-1133
DOI:
10.18653/v1/S18-1133
Bibkey:
Cite (ACL):
Sean MacAvaney, Luca Soldaini, Arman Cohan, and Nazli Goharian. 2018. GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 831–835, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification (MacAvaney et al., SemEval 2018)
Copy Citation:
PDF:
https://aclanthology.org/S18-1133.pdf
Code
 Georgetown-IR-Lab/semeval2018-task7