GenRES: Rethinking Evaluation for Generative Relation Extraction in the Era of Large Language Models

arXiv:2402.10744v1 Announce Type: new
Abstract: The field of relation extraction (RE) is experiencing a notable shift towards generative relation extraction (GRE), leveraging the capabilities of large language models (LLMs). However, we discovered that traditional relation extraction (RE) metrics like precision and recall fall short in evaluating GRE methods. This shortfall arises because these metrics rely on exact matching with human-annotated reference relations, while GRE methods often produce diverse and semantically accurate relations that differ from the references. To fill this …

abstract arxiv capabilities cs.ai cs.cl evaluation extraction generative language language models large language large language models llms metrics precision recall shift type