arXiv:1804.05408
공식 코드 · Papers with Code
GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Single Attention-Based Combination of CNN and RNN for Relation Classification
Comparative Analysis of AI Agent Architectures for Entity Relationship Classification
Towards a More Generalized Approach in Open Relation Extraction
Towards Rehearsal-Free Continual Relation Extraction: Capturing Within-Task Variance with Adaptive Prompting
Multistage Relation Network With Dual-Metric for Few-Shot Hyperspectral Image Classification
Semi-supervised Time Series Classification by Temporal Relation Prediction
토론
이 논문과 연결된 포럼 글이 아직 없습니다.