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Shengxuan Luo

2 accepted papers

2022

An Accurate Unsupervised Method for Joint Entity Alignment and Dangling Entity Detection

ACL 2022findings

Knowledge graph integration typically suffers from the widely existing dangling entities that cannot find alignment cross knowledge graphs (KGs). The dangling entity set is unavailable in most real-world scenarios, and manually mining the entity pairs that consist of entities with the same meaning i…

2022

Label Refinement via Contrastive Learning for Distantly-Supervised Named Entity Recognition

NAACL 2022findings

Distantly-supervised named entity recognition (NER) locates and classifies entities using only knowledge bases and unlabeled corpus to mitigate the reliance on human-annotated labels. The distantly annotated data suffer from the noise in labels, and previous works on DSNER have proved the importance…