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

2018-04-15 · SEMEVAL 2018 6 · Sean MacAvaney, Luca Soldaini, Arman Cohan, Nazli Goharian

SemEval 2018 Task 7 focuses on relation ex- traction 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.

📄 PDF Abstract BibTeX arXiv:1804.05408

Code (1)

Georgetown-IR-Lab/semeval2018-task7 공식 구현 mxnet

Tasks

ClassificationGeneral ClassificationRelationRelation Classification

Methods 이 논문이 사용한 방법론

Sigmoid Activation 설명 없음
Tanh Activation 설명 없음
LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

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