A pytorch version of ACL 2020 paper "A Novel Cascade Binary Tagging Framework for Relational Triple Extraction"
- 安装相关依赖
- 解压/datasets/NYT/NYT_normal_dataset.zip
- 创建目录/pretrained_models/bert-base-cased/
- 下载pytorch的bert模型,放入上述目录(下载链接见百度网盘)
pytorch bert-base-cased 模型:https://pan.baidu.com/s/1u4IC6ldMLf43oEQxF-SdLA 提取码:lv4y
- 解压/datasets/2019_Baidu_RE/2019_Baidu_RE.zip (数据集已处理过,原数据见百度网盘)
- 创建目录/pretrained_models/chinese-bert_chinese_wwm_pytorch/
- 下载哈工大预训练模型,放入上述目录(下载链接见讯飞网盘,哈工大git库中提供)
- 运行run.py --model chinese-bert --dataset 2019_Baidu_RE
chinese-bert_chinese_wwm_pytorch 模型:http://pan.iflytek.com/#/link/5DBDD89414E5B565D3322D6B7937DF47 提取码:hteX
百度2019语言与智能技术竞赛数据集 链接:https://pan.baidu.com/s/1aIxaccaLj9OhoRljN0ATpQ 提取码:gbua
原论文链接: https://arxiv.org/abs/1909.03227
tensorflow版本: https://github.com/weizhepei/CasRel
pytorch原版本:https://github.com/WeKnowG/Extractor
bert-chinese中文bert:https://github.com/ymcui/Chinese-BERT-wwm