Knowledge-Enhanced Relation Extraction Dataset

• URL: http://arxiv.org/abs/2210.11231v3
• Date: Tue, 25 Apr 2023 08:46:30 GMT
• Title: Knowledge-Enhanced Relation Extraction Dataset
• Authors: Yucong Lin, Hongming Xiao, Jiani Liu, Zichao Lin, Keming Lu, Feifei Wang, Wei Wei
• Abstract summary: There is currently no public dataset that encompasses both evidence sentences and knowledge graphs for knowledge-enhanced relation extraction. We introduce the Knowledge-Enhanced Relation Extraction dataset (KERED) KERED annotates each sentence with a relational fact, and it provides knowledge context for entities through entity linking.
• Score: 8.612433805862619
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recently, knowledge-enhanced methods leveraging auxiliary knowledge graphs have emerged in relation extraction, surpassing traditional text-based approaches. However, to our best knowledge, there is currently no public dataset available that encompasses both evidence sentences and knowledge graphs for knowledge-enhanced relation extraction. To address this gap, we introduce the Knowledge-Enhanced Relation Extraction Dataset (KERED). KERED annotates each sentence with a relational fact, and it provides knowledge context for entities through entity linking. Using our curated dataset, We compared contemporary relation extraction methods under two prevalent task settings: sentence-level and bag-level. The experimental result shows the knowledge graphs provided by KERED can support knowledge-enhanced relation extraction methods. We believe that KERED offers high-quality relation extraction datasets with corresponding knowledge graphs for evaluating the performance of knowledge-enhanced relation extraction methods. Our dataset is available at: \url{https://figshare.com/projects/KERED/134459}

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