Few-shot Named Entity Recognition via Superposition Concept Discrimination

arXiv:2403.16463v1 Announce Type: new
Abstract: Few-shot NER aims to identify entities of target types with only limited number of illustrative instances. Unfortunately, few-shot NER is severely challenged by the intrinsic precise generalization problem, i.e., it is hard to accurately determine the desired target type due to the ambiguity stemming from information deficiency. In this paper, we propose Superposition Concept Discriminator (SuperCD), which resolves the above challenge via an active learning paradigm. Specifically, a concept extractor is first introduced to identify …

abstract arxiv concept cs.cl discrimination few-shot identify information instances intrinsic ner recognition stemming superposition type types via