awesome-chinese-ner

中文命名实体识别

延申

• 中文预训练模型综述
  https://www.jsjkx.com/CN/10.11896/jsjkx.211200018
• 中文预训练模型下载地址
  https://github.com/lonePatient/awesome-pretrained-chinese-nlp-models
• 中文词向量下载地址
  https://github.com/Embedding/Chinese-Word-Vectors
• Bilstm_CRF怎么调参？
  https://arxiv.org/pdf/1707.06799.pdf
• 使用chatgpt进行信息抽取（实体、关系、事件）
  Zero-Shot Information Extraction via Chatting with ChatGPT
  演示地址：http://124.221.16.143:5000/
  https://arxiv.org/pdf/2302.10205.pdf
  https://github.com/cocacola-lab/ChatIE
  
• GPT for Information Extraction
  https://github.com/cocacola-lab/GPT4IE
  
• Evaluation-of-ChatGPT-on-Information-Extraction
  https://github.com/RidongHan/Evaluation-of-ChatGPT-on-Information-Extraction
  
• 这篇把它放在延申这里：
  Unified Text Structuralization with Instruction-tuned Language Models
  2023
  https://arxiv.org/pdf/2303.14956v2.pdf
  
• GPT-NER: Named Entity Recognition via Large Language Models
  2023
  https://arxiv.org/pdf/2304.10428v1.pdf
  https://github.com/ShuheWang1998/GPT-NER
  
• EasyInstruct: An Easy-to-use Framework to Instruct Large Language Models
  https://github.com/zjunlp/EasyInstruct
• CODEIE: Large Code Generation Models are Better Few-Shot Information Extractors
  在代码中进行实体和关系的提取
  2023
  https://arxiv.org/pdf/2305.05711v1.pdf
  https://github.com/dasepli/CodeIE
  
• PromptNER : Prompting For Named Entity Recognition
  2023
  https://arxiv.org/pdf/2305.15444v2.pdf
  

命名实体识别综述（中文）

• 基于深度学习的中文命名实体识别最新研究进展综述
  2022年 中文信息学报
  http://61.175.198.136:8083/rwt/125/http/GEZC6MJZFZZUPLSSGM3B/Qikan/Article/Detail?id=7107633068
  
• 命名实体识别方法研究综述
  2022年 计算机科学与探索
  http://fcst.ceaj.org/CN/10.3778/j.issn.1673-9418.2112109
  
• 中文命名实体识别综述
  2021年 计算机科学与探索
  http://fcst.ceaj.org/CN/abstract/abstract2902.shtml
  
• Chinese named entity recognition: The state of the art
  Neurocomputing 2022
  link

模型

• Attack Named Entity Recognition by Entity Boundary Interference
  2023
  https://arxiv.org/pdf/2305.05253v1.pdf
  

• Token Relation Aware Chinese Named Entity Recognition
  ACM Transactions on Asian and Low-Resource Language Information Processing 2023
  https://dl.acm.org/doi/10.1145/3531534
  

• PUnifiedNER: a Prompting-based Unified NER System for Diverse Datasets
  AAAI 2023
  https://arxiv.org/pdf/2211.14838.pdf
  https://github.com/GeorgeLuImmortal/PUnifiedNER
  

• END-TO-END ENTITY DETECTION WITH PROPOSER ANDREGRESSOR
  借鉴目标检测的思想
  2022
  https://arxiv.org/pdf/2210.10260v2.pdf
  https://github.com/Rosenberg37/EntityDetection
  

• DAMO-NLP at SemEval-2022 Task 11:A Knowledge-based System for Multilingual Named Entity Recognition
  多语言的命名实体识别
  2022
  https://arxiv.org/pdf/2203.00545.pdf
  https://github.com/Alibaba-NLP/KB-NER
  

• PCBERT: Parent and Child BERT for Chinese Few-shot NER
  COLING 2022
  https://aclanthology.org/2022.coling-1.192.pdf

• GNN-SL: Sequence Labeling Based on Nearest Examples via GNN
  2022
  https://arxiv.org/pdf/2212.02017.pdf
  https://github.com/ShuheWang1998/GNN-SL

• EiCi: A New Method of Dynamic Embedding Incorporating Contextual Information in Chinese NER
  这个和AMBERT的思想感觉差不多：AMBERT
  2022
  https://openreview.net/pdf?id=0TKg4UlnEEQ

• Deep Span Representations for Named Entity Recognition
  2022
  https://arxiv.org/pdf/2210.04182v1.pdf

• Mulco: Recognizing Chinese Nested Named Entities Through Multiple Scopes
  2022
  https://arxiv.org/pdf/2211.10854.pdf

• Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence Labeling
  EMNLP 2022
  https://arxiv.org/pdf/2210.15231.pdf
  http://github.com/modelscope/adaseq/examples/babert

• Domain-Specific NER via Retrieving Correlated Samples
  COLING 2022
  https://arxiv.org/pdf/2208.12995.pdf

• Two Languages Are Better than One: Bilingual Enhancement for Chinese Named Entity Recognition
  COLING 2022
  https://aclanthology.org/2022.coling-1.176.pdf

• A hybrid Transformer approach for Chinese NER with features augmentation
  Expert Syst. Appl 2022
  https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4087645

• Adaptive Threshold Selective Self-Attention for Chinese NER
  COLING 2022
  https://aclanthology.org/2022.coling-1.157.pdf

• Improving Chinese Named Entity Recognition by Search Engine Augmentation
  2022
  https://arxiv.org/pdf/2210.12662.pdf
  

• Domain-Specific NER via Retrieving Correlated Samples
  COLING 2022
  https://arxiv.org/pdf/2208.12995.pdf
  

• Robust Self-Augmentation for Named Entity Recognition with Meta Reweighting
  NAACL 2022
  https://arxiv.org/pdf/2204.11406.pdf
  https://github.com/LindgeW/MetaAug4NER
  

• Boundary Smoothing for Named Entity Recognition
  ACL 2022
  https://arxiv.org/pdf/2204.12031v1.pdf
  https://github.com/syuoni/eznlp
  

• NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
  2022
  https://arxiv.org/pdf/2205.05832.pdf
  

• Unified Structure Generation for Universal Information Extraction
  （一统实体识别、关系抽取、事件抽取、情感分析），百度UIE
  ACL 2022
  https://arxiv.org/pdf/2203.12277.pdf
  https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/uie
  https://github.com/universal-ie/UIE
  以下这篇也是通用的，只是英文方面的，没有中文数据上的实验：

  • DEEPSTRUCT: Pretraining of Language Models for Structure Prediction
    2022
    https://arxiv.org/pdf/2205.10475v1.pdf
    https://github.com/cgraywang/deepstruct
    

• Parallel Instance Query Network for Named Entity Recognition
  2022
  https://arxiv.org/pdf/2203.10545v1.pdf
  

• Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition
  NAACL 2022
  https://arxiv.org/pdf/2204.05544.pdf
  

• TURNER: The Uncertainty-based Retrieval Framework for Chinese NER
  2022
  https://arxiv.org/pdf/2202.09022
  

• NN-NER: Named Entity Recognition with Nearest Neighbor Search
  2022
  https://arxiv.org/pdf/2203.17103
  https://github.com/ShannonAI/KNN-NER
  

• Unified Named Entity Recognition as Word-Word Relation Classification
  AAAI 2022
  https://arxiv.org/abs/2112.10070
  https://github.com/ljynlp/W2NER.git
  

• MarkBERT: Marking Word Boundaries Improves Chinese BERT
  2022
  https://arxiv.org/pdf/2203.06378
  

• MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition
  2021
  https://arxiv.org/pdf/2109.07877
  

• AdaK-NER: An Adaptive Top-K Approach for Named Entity Recognition with Incomplete Annotations
  2021
  https://arxiv.org/pdf/2109.05233
  

• ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information
  ACL 2021
  https://arxiv.org/pdf/2106.16038
  https://github.com/ShannonAI/ChineseBert
  

• Enhanced Language Representation with Label Knowledge for Span Extraction
  EMNLP 2021
  https://aclanthology.org/2021.emnlp-main.379.pdf
  https://github.com/Akeepers/LEAR
  

• Lex-BERT: Enhancing BERT based NER with lexicons
  ICLR 2021
  https://arxiv.org/pdf/2101.00396v1.pdf
  

• Lexicon Enhanced Chinese Sequence Labeling Using BERT Adapter
  ACL 2021
  https://arxiv.org/pdf/2105.07148.pdf
  https://github.com/liuwei1206/LEBERT
  

• MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition
  ACL 2021
  https://arxiv.org/pdf/2107.05418v1.pdf
  https://github.com/CoderMusou/MECT4CNER
  

• Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition
  ACL 2021
  https://arxiv.org/pdf/2105.06804v2.pdf
  https://github.com/tricktreat/locate-and-label
  

• Dynamic Modeling Cross- and Self-Lattice Attention Network for Chinese NER
  AAAI 2021
  https://ojs.aaai.org/index.php/AAAI/article/view/17706/17513
  https://github.com/zs50910/DCSAN-for-Chinese-NER
  

• Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
  EMNLP-2020
  https://arxiv.org/pdf/2010.15466
  https://github.com/cuhksz-nlp/AESINER
  

• ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
  ACL 2020
  https://arxiv.org/pdf/1911.00720v1.pdf
  https://github.com/sinovation/ZEN
  

• A Unified MRC Framework for Named Entity Recognition
  ACL 2020
  https://arxiv.org/pdf/1910.11476v6.pdf
  https://github.com/ShannonAI/mrc-for-flat-nested-ner
  

• Simplify the Usage of Lexicon in Chinese NER
  ACL 2020
  https://arxiv.org/pdf/1908.05969.pdf
  https://github.com/v-mipeng/LexiconAugmentedNER
  

• A Boundary Regression Model for Nested Named Entity Recognition
  2020
  https://arxiv.org/pdf/2011.14330v3.pdf
  https://github.com/yuelfei/BR
  

• Dice Loss for Data-imbalanced NLP Tasks
  ACL 2020
  https://arxiv.org/pdf/1911.02855v3.pdf
  https://github.com/ShannonAI/dice_loss_for_NLP
  

• Porous Lattice Transformer Encoder for Chinese NER
  COLING 2020
  https://aclanthology.org/2020.coling-main.340.pdf
  

• FLAT: Chinese NER Using Flat-Lattice Transformer
  ACL 2020
  https://arxiv.org/pdf/2004.11795v2.pdf
  https://github.com/LeeSureman/Flat-Lattice-Transformer
  

• FGN: Fusion Glyph Network for Chinese Named Entity Recognition
  2020
  https://arxiv.org/pdf/2001.05272v6.pdf
  https://github.com/AidenHuen/FGN-NER
  

• SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
  2020
  https://arxiv.org/pdf/2007.08416v1.pdf
  https://github.com/zerohd4869/SLK-NER
  

• Entity Enhanced BERT Pre-training for Chinese NER
  EMNLP 2020
  https://aclanthology.org/2020.emnlp-main.518.pdf
  https://github.com/jiachenwestlake/Entity_BERT
  

• Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
  ACL2020
  https://arxiv.org/pdf/2010.15466v1.pdf
  https://github.com/cuhksz-nlp/AESINER
  

• Named Entity Recognition for Social Media Texts with Semantic Augmentation
  EMNLP 2020
  https://arxiv.org/pdf/2010.15458v1.pdf
  https://github.com/cuhksz-nlp/SANER
  

• CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
  2020
  https://arxiv.org/pdf/2001.04351v4.pdf
  https://github.com/CLUEbenchmark/CLUENER2020
  

• ERNIE: Enhanced Representation through Knowledge Integration
  2019
  https://arxiv.org/pdf/1904.09223v1.pdf
  https://github.com/PaddlePaddle/ERNIE
  

• TENER: Adapting Transformer Encoder for Named Entity Recognition
  2019
  https://arxiv.org/pdf/1911.04474v3.pdf
  https://github.com/fastnlp/TENER
  

• Chinese NER Using Lattice LSTM
  ACL 2018
  https://arxiv.org/pdf/1805.02023v4.pdf
  https://github.com/jiesutd/LatticeLSTM
  

• ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
  2019
  https://arxiv.org/pdf/1907.12412v2.pdf
  https://github.com/PaddlePaddle/ERNIE
  

• Glyce: Glyph-vectors for Chinese Character Representations
  NeurIPS 2019
  https://arxiv.org/pdf/1901.10125v5.pdf
  https://github.com/ShannonAI/glyce
  

• CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
  NAACL 2019
  https://arxiv.org/pdf/1904.02141v3.pdf
  https://github.com/microsoft/vert-papers/tree/master/papers/CAN-NER
  

• Neural Chinese Named Entity Recognition via CNN-LSTM-CRF and Joint Training with Word Segmentation
  2019
  https://arxiv.org/pdf/1905.01964v1.pdf
  https://github.com/rxy007/cnn-lstm-crf
  

• Chinese Named Entity Recognition Augmented with Lexicon Memory
  2019
  https://arxiv.org/pdf/1912.08282v2.pdf
  https://github.com/dugu9sword/LEMON
  

• Exploiting Multiple Embeddings for Chinese Named Entity Recognition
  2019
  https://arxiv.org/pdf/1908.10657v1.pdf
  https://github.com/WHUIR/ME-CNER
  

• Dependency-Guided LSTM-CRF for Named Entity Recognition
  IJCNLP 2019
  https://arxiv.org/pdf/1909.10148v1.pdf
  https://github.com/allanj/ner_with_dependency
  

• CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
  NAACL-HLT (1) 2019
  https://aclanthology.org/N19-1342/
  

• CNN-Based Chinese NER with Lexicon Rethinking
  IJCAI 2019
  https://www.ijcai.org/proceedings/2019/0692.pdf
  https://aclanthology.org/N19-1342.pdf
  

• Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network
  IJCNLP 2019
  https://aclanthology.org/D19-1396.pdf
  https://github.com/DianboWork/Graph4CNER
  

• Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning
  COLING 2018
  https://aclanthology.org/C18-1183.pdf
  https://github.com/rainarch/DSNER
  

• Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism
  EMNLP 2018
  https://aclanthology.org/D18-1017.pdf
  https://github.com/CPF-NLPR/AT4ChineseNER
  

非中文模型

没有针对于中文的实验，但是思想可以借鉴的：

• DiffusionNER: Boundary Diffusion for Named Entity Recognition
  2023
  https://arxiv.org/pdf/2305.13298v1.pdf
  https://github.com/tricktreat/DiffusionNER
  
• Learning In-context Learning for Named Entity Recognition
  ACL 2023
  https://arxiv.org/pdf/2305.11038v1.pdf
  https://github.com/chen700564/metaner-icl
  
• UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective
  2023
  https://arxiv.org/pdf/2305.10306v1.pdf
  
• Easy-to-Hard Learning for Information Extraction∗
  2023
  https://arxiv.org/pdf/2305.09193v1.pdf
  https://github.com/DAMO-NLP-SG/IE-E2H
  
• UTC-IE: A Unified Token-pair Classification Architecture for Information Extraction
  2023
  https://openreview.net/pdf?id=cRQwl-59CU8
  https://github.com/yhcc/utcie
  
• Deep Span Representations for Named Entity Recognition
  Boundary Smoothing for Named Entity Recognition(同作者)
  ACL 2023
  https://github.com/syuoni/eznlp
  https://arxiv.org/pdf/2210.04182v2.pdf
  
• NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension
  2023
  https://arxiv.org/pdf/2305.03970v1.pdf
  
• RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction
  通用信息抽取，对比USM
  2023
  https://arxiv.org/pdf/2304.14770.pdf
  
• InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction
  （又一篇通用信息抽取，对比百度UIE以及USM）
  2023
  https://arxiv.org/pdf/2304.08085v1.pdf
  https://github.com/BeyonderXX/InstructUIE
  
• Universal Information Extraction as Unified Semantic Matching
  通用的信息抽取：实体、关系、事件（没有在中文数据上的实验），简称USM
  AAAI 2023
  https://arxiv.org/pdf/2301.03282.pdf
  
• MULTI-TASK TRANSFORMER WITH RELATION-ATTENTION AND TYPE-ATTENTION FOR NAMED ENTITY RECOGNITION
  2023
  https://arxiv.org/pdf/2303.10870v1.pdf
  
• DEEPSTRUCT: Pretraining of Language Models for Structure Prediction
  通用信息抽取
  ACL 2022
  https://arxiv.org/pdf/2205.10475v2.pdf
  https://github.com/cgraywang/deepstruct
  
• TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags
  改进W2NER模型
  IEEE TASLP(Transactions on Audio, Speech and Language Processing)
  https://arxiv.org/pdf/2211.00684.pdf
  https://github.com/solkx/TOE
  
• OPTIMIZING BI-ENCODER FOR NAMED ENTITY RECOGNITION VIA CONTRASTIVE LEARNING
  ICLR 2023
  https://arxiv.org/pdf/2208.14565v2.pdf
  github.com/microsoft/binder
  
• One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER
  2023
  https://arxiv.org/pdf/2301.10410v2.pdf
  https://github.com/zjunlp/DeepKE/tree/main/example/ner/cross
  
• QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition
  2022
  https://arxiv.org/pdf/2203.01543.pdf
  
• A Unified Generative Framework for Various NER Subtasks
  （使用BART生成模型进行命名实体识别）
  ACL-ICJNLP 2021
  https://arxiv.org/pdf/2106.01223.pdf
  https://github.com/yhcc/BARTNER
  (以下四篇是基于prompt的命名实体识别)
  
• Template-Based Named Entity Recognition Using BART
  https://arxiv.org/abs/2106.01760
  https://github.com/Nealcly/templateNER
  
• Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER
  https://arxiv.org/abs/2110.08454
  https://github.com/INK-USC/fewNER
  
• LightNER: A Lightweight Generative Framework with Prompt-guided Attention for Low-resource NER
  https://arxiv.org/abs/2109.00720
  https://github.com/zjunlp/DeepKE/blob/main/example/ner/few-shot/README_CN.md
  
• Template-free Prompt Tuning for Few-shot NER
  https://arxiv.org/abs/2109.13532
  https://github.com/rtmaww/EntLM/
  

数据集

• MSRA
• Weibo
• resume
• onenotes4
• onenotes5
• 一家公司提供的数据集,包含人名、地名、机构名、专有名词。
• 人民网（04年）
• 影视-音乐-书籍实体标注数据
• 中文医学文本命名实体识别 2020CCKS
• 医渡云实体识别数据集
• CLUENER2020
• 不同任务中文数据集整理
• 医疗相关的数据集
• 30+ner数据汇总
• 中文实体识别数据集汇总

预训练语言模型

• ChineseBert ACL2021
• MacBert 2020
• SpanBert
• XLNet
• Roberta
• Bert
• StructBert
• WoBert
• ELECTRA
• Ernie1.0
• Ernie2.0
• Ernie3.0
• ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding
• NeZha
• MengZi
• ZEN
• ALBERT
• roformer
• roformer-v2
• Pretraining without Wordpieces: Learning Over a Vocabulary of Millions of Words
• PERT: Pre-Training BERT with Permuted Language Model
• RoChBert: Towards Robust BERT Fine-tuning for Chinese EMNLP2022
• MarkBERT: Marking Word Boundaries Improves Chinese BERT 2022
• MVP-BERT: REDESIGNING VOCABULARIES FOR CHINESE BERT AND MULTI-VOCAB PRETRAINING 2022
• LERT: A Linguistically-motivated Pre-trained Language Model 2022
• AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization 2022
• BURT: BERT-inspired Universal Representation from Learning Meaningful Segment 2021
• Towards Efficient NLP: A Standard Evaluation and A Strong Baseline
• Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
• AdaSeq: An All-in-One Library for Developing State-of-the-Art Sequence Understanding Models 多种方法
• TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning NAACL 2022
• Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models 2023
• MiniRBT: A Two-stage Distilled Small Chinese Pre-trained Model 2023
• sikuGPT 古文模型 2023
• UniIE 通用信息抽取

Ner工具

• Stanza
• LAC
• Ltp 哈工大
• Hanlp
• foolnltk
• NLTK
• BosonNLP
• FudanNlp 复旦大学
• Jionlp
• HarvestText
• fastHan
• EsayNLP 阿里巴巴
• PaddleNLP 百度
• AliceMind 阿里巴巴
• spacy
• DeepKE
• coreNlp JAVA/Python
• opennlp JAVA
• NLPIR
• trankit 多语言
• HugIE 通用信息抽取
• EasyInstruct

比赛

• CCKS2017开放的中文的电子病例测评相关的数据。
  评测任务一：https://biendata.com/competition/CCKS2017_1/
  评测任务二：https://biendata.com/competition/CCKS2017_2/
  
• CCKS2018开放的音乐领域的实体识别任务。
  评测任务：https://biendata.com/competition/CCKS2018_2/
  
• (CoNLL 2002)Annotated Corpus for Named Entity Recognition。
  地址：https://www.kaggle.com/abhinavwalia95/entity-annotated-corpus
  
• NLPCC2018开放的任务型对话系统中的口语理解评测。
  地址：http://tcci.ccf.org.cn/conference/2018/taskdata.php
  
• 非结构化商业文本信息中隐私信息识别
  地址：https://www.datafountain.cn/competitions/472/datasets
• 商品标题识别
  地址：https://www.heywhale.com/home/competition/620b34ed28270b0017b823ad/content/3
• CCKS2021中文NLP地址要素解析
  地址：https://tianchi.aliyun.com/competition/entrance/531900/introduction
• CAIL2022信息抽取赛道
  地址：http://cail.cipsc.org.cn/task6.html?raceID=6&cail_tag=2022
• 2019互联网金融新实体发现
  
• 2020CHIP-中药说明书实体识别挑战
  
• 2020CHIP-中文医学文本命名实体识别
  
• 2020CCKS面向试验鉴定的命名实体识别
  
• 2020CCKS面向中文电子病历的医疗实体及事件抽取-子任务1：医疗命名实体识别
• LAIC2022-犯罪事实实体识别
• SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)
• 新型电力系统人工智能应用大赛赛题二：电力生产知识图谱多模式信息抽取
• CCKS2022通用信息抽取