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天池中药说明书实体识别挑战冠军方案；中文命名实体识别；NER; BERT-CRF & BERT-SPAN & BERT-MRC；Pytorch
基于pytorch的多头选择方法进行中文命名实体识别。
基于Pytorch的BERT-IDCNN-BILSTM-CRF中文实体识别实现
基于Tensorflow2.3开发的NER模型，都是CRF范式，包含Bilstm(IDCNN)-CRF、Bert-Bilstm(IDCNN)-CRF、Bert-CRF，可微调预训练模型，可对抗学习，用于命名实体识别，配置后可直接运行。
pytorch实现 基于Bert+BiLSTM+CRF的中文命名实体识别
Chinese NER using Lattice LSTM. Code for ACL 2018 paper.
文本挖掘和预处理工具（文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等），无监督或弱监督方法
Comparison of Chinese Named Entity Recognition Models between NeuroNER and BertNER
RoBERTa + BiLSTM + CRF for Chinese NER Task
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
An implement of the paper of EDA for Chinese corpus.中文语料的EDA数据增强工具。NLP数据增强。论文阅读笔记。
Use Google's BERT for named entity recognition （CoNLL-2003 as the dataset）.
本项目采用PyTorch和transformers模块实现英语序列标注，其中对BERT进行微调。
An implementation of BERT for cybersecurity named entity recognition
Named-Entity-Recognition for Cybersecurity. This repository contains code for fine-tuning a pretrained ner model with custom dataset
provides a new dataset for NER missions in cyber threat intelligence (CTI) field.
中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）
Enhancing Cyber Threat Intelligence with Named Entity Recognition using BERT-CRF
Fine-tuned a pre-trained BERT model for Named Entity Recognition task in the cybersecurity domain.
PyTorch code for paper, 'Split-NER: Named Entity Recognition via Two Question-Answering-based Classifications', ACL'23
This is a project source for NER in cybersecurity threat intelligence