Web: http://arxiv.org/abs/2205.02225

May 5, 2022, 1:11 a.m. | Shuliang Liu, Xuming Hu, Chenwei Zhang, Shu`ang Li, Lijie Wen, Philip S. Yu

cs.CL updates on arXiv.org arxiv.org

Unsupervised relation extraction aims to extract the relationship between
entities from natural language sentences without prior information on
relational scope or distribution. Existing works either utilize self-supervised
schemes to refine relational feature signals by iteratively leveraging adaptive
clustering and classification that provoke gradual drift problems, or adopt
instance-wise contrastive learning which unreasonably pushes apart those
sentence pairs that are semantically similar. To overcome these defects, we
propose a novel contrastive learning framework named HiURE, which has the
capability to derive …

arxiv extraction hierarchical learning unsupervised

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