Few-Shot Relation Extraction Through Prompt With Relation Information and Multi-Level Contrastive Learning
Author:
Affiliation:
1. School of Computer Science and Technology, Xinjiang University, Ürömqi, China
2. Department of Nursing, Fifth Affiliated Hospital of Xinjiang Medical University, Ürömqi, China
Funder
Natural Science Foundation of Xinjiang Uygur Autonomous Region, Application Research on Assisted Intelligent Care for Inpatients Based on Electronic Medical Records
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10662978.pdf?arnumber=10662978
Reference36 articles.
1. A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers
2. Question Answering with Subgraph Embeddings
3. Learning Knowledge Graph Embedding With Heterogeneous Relation Attention Networks
4. Relation Classification via Multi-Level Attention CNNs
5. FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
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