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Found 5 papers, 1 papers with code
Improving Discriminative Learning for Zero-Shot Relation Extraction
Zero-shot relation extraction (ZSRE) aims to predict target relations that cannot be observed during training.
Ranked #3 on
Zero-shot Relation Classification
on FewRel
Enhancing Semantic Correlation between Instances and Relations for Zero-Shot Relation Extraction
This study argues that enhancing the semantic correlation between instances and relations is key to effectively solving the zero-shot relation extraction task.
Ranked #1 on
Zero-shot Relation Classification
on FewRel
Improved Decomposition Strategy for Joint Entity and Relation Extraction
A recent study (Yu et al. 2020) proposed a novel decomposition strategy that splits the task into two interrelated subtasks: detection of the head-entity (HE) and identification of the corresponding tail-entity and relation (TER) for each extracted head-entity.
CovRelex: A COVID-19 Retrieval System with Relation Extraction
This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers.
Relation Classification Using Segment-Level Attention-based CNN and Dependency-based RNN
Recently, relation classification has gained much success by exploiting deep neural networks.
