Grasping the Essentials: Tailoring Large Language Models for Zero-Shot Relation Extraction

arXiv:2402.11142v1 Announce Type: new
Abstract: Relation extraction (RE), a crucial task in NLP, aims to identify semantic relationships between entities mentioned in texts. Despite significant advancements in this field, existing models typically rely on extensive annotated data for training, which can be both costly and time-consuming to acquire. Moreover, these models often struggle to adapt to new or unseen relationships. In contrast, few-shot learning settings, which aim to reduce annotation requirements, may offer incomplete and biased supervision for understanding target …

abstract annotated data arxiv cs.cl data extraction identify language language models large language large language models nlp relationships semantic training type zero-shot