AutoRE: Document-Level Relation Extraction with Large Language Models

arXiv:2403.14888v1 Announce Type: new
Abstract: Large Language Models (LLMs) have demonstrated exceptional abilities in comprehending and generating text, motivating numerous researchers to utilize them for Information Extraction (IE) purposes, including Relation Extraction (RE). Nonetheless, most existing methods are predominantly designed for Sentence-level Relation Extraction (SentRE) tasks, which typically encompass a restricted set of relations and triplet facts within a single sentence. Furthermore, certain approaches resort to treating relations as candidate choices integrated into prompt templates, leading to inefficient processing and …

abstract arxiv cs.ai cs.cl document extraction information information extraction language language models large language large language models llms researchers set tasks text them type