mlsanityData to 14 Oct 2026

DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population

arXiv 2201.03335 ↗First posted 10 Jan 2022cs.CL cs.AI cs.IRcited by 17

Not on the map. Why?

Abstract (arXiv)

We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population. DeepKE implements various information extraction tasks, including named entity recognition, relation extraction and attribute extraction. With a unified framework, DeepKE allows developers and researchers to customize datasets and models to extract information from unstructured data according to their requirements. Specifically, DeepKE not only provides various functional modules and model implementation for different tasks and scenarios but also organizes all components by consistent frameworks to maintain sufficient modularity and extensibility. We release the source code at GitHub in https://github.com/zjunlp/DeepKE with Google Colab tutorials and comprehensive documents for beginners. Besides, we present an online system in http://deepke.openkg.cn/EN/re_doc_show.html for real-time extraction of various tasks, and a demo video.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 48 of its 92 references that are in the map. First posted on arXiv 10 Jan 2022.

Builds on

48 of 92 references.

References · 48

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  6. 2019ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Taskscited by 2,222
  7. 2021PTR: Prompt Tuning with Rules for Text Classificationcited by 238
  8. 2019KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoningcited by 216
  9. 2021KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extractioncited by 180
  10. 2021Template-Based Named Entity Recognition Using BARTcited by 153
  11. 2018Graph Convolution over Pruned Dependency Trees Improves Relation Extractioncited by 146
  12. 2021A Unified Generative Framework for Various NER Subtaskscited by 141
36 more
  1. 2018DKN: Deep Knowledge-Aware Network for News Recommendationcited by 137
  2. 2020Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Poolingcited by 115
  3. 2021Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learnerscited by 115
  4. 2020Reasoning with Latent Structure Refinement for Document-Level Relation Extractioncited by 97
  5. 2020Double Graph Based Reasoning for Document-level Relation Extractioncited by 87
  6. 2020Coreferential Reasoning Learning for Language Representationcited by 80
  7. 2021Document-level Relation Extraction as Semantic Segmentationcited by 80
  8. 2019OpenNRE: An Open and Extensible Toolkit for Neural Relation Extractioncited by 62
  9. 2019Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networkscited by 61
  10. 2019Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detectioncited by 54
  11. 2020Contrastive Triple Extraction with Generative Transformercited by 44
  12. 2020Global-to-Local Neural Networks for Document-Level Relation Extractioncited by 43
  13. 2020HIN: Hierarchical Inference Network for Document-Level Relation Extractioncited by 42
  14. 2020Document-Level Relation Extraction with Reconstructioncited by 41
  15. 2020Few-Shot Named Entity Recognition: A Comprehensive Studycited by 41
  16. 2021PRGC: Potential Relation and Global Correspondence Based Joint Relational Triple Extractioncited by 40
  17. 2021Curriculum-Meta Learning for Order-Robust Continual Relation Extractioncited by 34
  18. 2021AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibabacited by 33
  19. 2020N-LTP: An Open-source Neural Language Technology Platform for Chinesecited by 29
  20. 2020GDPNet: Refining Latent Multi-View Graph for Relation Extractioncited by 29
  21. 2021Noisy-Labeled NER with Confidence Estimationcited by 28
  22. 2019Label-Agnostic Sequence Labeling by Copying Nearest Neighborscited by 27
  23. 2021LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Promptingcited by 27
  24. 2019Relation Adversarial Network for Low Resource Knowledge Graph Completioncited by 24
  25. 2021OntoED: Low-resource Event Detection with Ontology Embeddingcited by 23
  26. 2021SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysiscited by 23
  27. 2020Example-Based Named Entity Recognitioncited by 19
  28. 2020Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extractioncited by 18
  29. 2021MLBiNet: A Cross-Sentence Collective Event Detection Networkcited by 15
  30. 2019When Low Resource NLP Meets Unsupervised Language Model: Meta-pretraining Then Meta-learning for Few-shot Text Classificationcited by 13
  31. 2020Finding Influential Instances for Distantly Supervised Relation Extractioncited by 13
  32. 2020On Robustness and Bias Analysis of BERT-based Relation Extractioncited by 10
  33. 2021Learning to Ask for Data-Efficient Event Argument Extractioncited by 5
  34. 2021LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with Self-trainingcited by 5
  35. 2021Normal vs. Adversarial: Salience-based Analysis of Adversarial Samples for Relation Extractioncited by 4
  36. 2019Context-aware Deep Model for Entity Recommendation in Search Engine at Alibabacited by 1

Built on by

Cited by year

Citing papers per year: 2022: 6; 2023: 8; 2024: 0; 2025: 3.

17 papers.

Sort:

By area:

  1. 2022OntoProtein: Protein Pretraining With Gene Ontology Embeddingcited by 70
  2. 2023MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Taskscited by 66
  3. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  4. 2022Ontology-enhanced Prompt-tuning for Few-shot Learningcited by 24
  5. 2023One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NERcited by 11
  6. 2023OmniEvent: A Comprehensive, Fair, and Easy-to-Use Toolkit for Event Understandingcited by 11
  7. 2022Information Extraction in Low-Resource Scenarios: Survey and Perspectivecited by 10
  8. 2022LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddingscited by 5
  9. 2025Event Extraction in Large Language Modelcited by 5
  10. 2025RAKG:Document-level Retrieval Augmented Knowledge Graph Constructioncited by 4
  11. 2023FRACAS: A FRench Annotated Corpus of Attribution relations in newScited by 3
  12. 2022gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpuscited by 2
5 more
  1. 2023CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Constructioncited by 2
  2. 2023A Concept Knowledge Graph for User Next Intent Prediction at Alipaycited by 1
  3. 2023Dynamic Multi-View Fusion Mechanism For Chinese Relation Extractioncited by 1
  4. 2025Are Large Language Models Effective Knowledge Graph Constructors?cited by 1
  5. 2023Semantic Information Extraction for Text Data with Probability Graphcited by 0