Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism
An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)
CCKS2019中文命名实体识别任务。从医疗文本中识别疾病和诊断、解剖部位、影像检查、实验室检验、手术和药物6种命名实体。现已实现基于jieba和AC自动机的baseline构建、基于BiLSTM和CRF的序列标住模型构建。bert的部分代码主要源于https://github.com/charles9n/bert-sklearn.git 感谢作者。 模型最终测试集得分0.81,还有较大改进空间。可以当做一个baseline。
Tensorflow solution of NER task Using BiLSTM-CRF model with CMU/Google XLNet
Named Entity Recognition for Chinese social media (Weibo). From EMNLP 2015 paper.
Chinese, English NER, English-Chinese machine translation dataset. 中英文实体识别数据集,中英文机器翻译数据集
A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)
本项目的数据来自“互联网新闻情感分析”赛题。基于Transformer2.0库中的中文Bert模型,对新闻语料进行三分类。