C-ICL: Contrastive In-context Learning for Information Extraction

arXiv:2402.11254v1 Announce Type: new
Abstract: Recently, there has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related to named entity recognition (NER) and relation extraction (RE). Although researchers are exploring the use of few-shot information extraction through in-context learning with LLMs, they tend to focus only on using correct or positive examples for demonstration, neglecting the potential value of incorporating incorrect or negative examples …

abstract advanced arxiv capabilities context cs.cl extraction few-shot in-context learning information information extraction language language models large language large language models llms ner recognition researchers tasks through type