BioGPT is a biomedical large language model and domain-specific transformer designed for processing and creating specialized medical text. It functions as a generative tool and knowledge extraction engine trained on large-scale scientific literature to produce human-like scientific prose and factual responses to queries. The project provides specialized capabilities for biomedical named entity recognition and the extraction of complex relations from unstructured medical corpora. It is designed to identify and classify biological entities through data mining and relation extraction to support
Universal Information Extraction, codes for the NeurIPS-2022 paper: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model.
Code and prompt templates for evaluation-filtering Some data were not uploaded due to size restrictions, but you can find all the datasets covered in this paper by the references in the paper.
Read this in English. 本仓库基于LLaMA-Factory代码，实现了基于大语言模型的文档级关系抽取系统AutoRE。使用的抽取范式为RHF（论文链接）。 目前基于Re-DocRED数据集进行实验，能够抽取文档级文本中的96个关系的三元组事实。