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Zero-shot Relation Triplet Extraction

2개 벤치마크 · 논문 5편 · 이 태스크의 논문 보기 →

Benchmarks

FewRel

결과 3개

Wiki-ZSL

결과 2개

Most implemented

Papers

Generative Meta-Learning for Zero-Shot Relation Triplet Extraction

2023-05-03 · Wanli Li, Tieyun Qian

The zero-shot relation triplet extraction (ZeroRTE) task aims to extract relation triplets from a piece of text with unseen relation types. The seminal work adopts the pre-trained generative model to generate synthetic s…

General KnowledgeMeta-LearningRelationTriplet+1

Zero-shot Triplet Extraction by Template Infilling

2022-12-21 · Bosung Kim, Hayate Iso, Nikita Bhutani, Estevam Hruschka 외

The task of triplet extraction aims to extract pairs of entities and their corresponding relations from unstructured text. Most existing methods train an extraction model on training data involving specific target relati…

Data AugmentationLanguage ModelingLanguage ModellingTriplet+2

PCRED: Zero-shot Relation Triplet Extraction with Potential Candidate Relation Selection and Entity Boundary Detection

2022-11-26 · Yuquan Lan, Dongxu Li, Yunqi Zhang, Hui Zhao 외

Zero-shot relation triplet extraction (ZeroRTE) aims to extract relation triplets from unstructured texts under the zero-shot setting, where the relation sets at the training and testing stages are disjoint. Previous sta…

Boundary DetectionRelationTripletZero-shot Relation Triplet Extraction

RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction

2022-03-17 · Findings (ACL) 2022 5 · Yew Ken Chia, Lidong Bing, Soujanya Poria, Luo Si

Despite the importance of relation extraction in building and representing knowledge, less research is focused on generalizing to unseen relations types. We introduce the task setting of Zero-Shot Relation Triplet Extrac…

Language ModelingLanguage ModellingRelationRelation Classification+5

Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders

2020-10-08 · EMNLP 2020 11 · Jue Wang, Wei Lu

Named entity recognition and relation extraction are two important fundamental problems. Joint learning algorithms have been proposed to solve both tasks simultaneously, and many of them cast the joint task as a table-fi…

Joint Entity and Relation Extractionnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+4