Chain of Thought with Explicit Evidence Reasoning for Few-shot Relation Extraction

arXiv:2311.05922v3 Announce Type: replace
Abstract: Few-shot relation extraction involves identifying the type of relationship between two specific entities within a text, using a limited number of annotated samples. A variety of solutions to this problem have emerged by applying meta-learning and neural graph techniques which typically necessitate a training process for adaptation. Recently, the strategy of in-context learning has been demonstrating notable results without the need of training. Few studies have already utilized in-context learning for zero-shot information extraction. Unfortunately, …

abstract arxiv chain of thought cs.cl evidence extraction few-shot graph meta meta-learning reasoning relationship samples solutions text thought training type