A curated collection of knowledge graph learning resources, including papers, tutorials, datasets, implementations, tools, and communities.
Resources are available in both English and Chinese. The language of each resource is indicated when it may not be clear from the title.
Link status: All links were checked on August 26, 2026. Contributions that report broken links or improve the organization of the list are welcome.
Date convention: The year shown for each resource is its latest meaningful update: recent repository or collection activity for maintained projects, and the publication or revision year for static papers, datasets, tutorials, and slides. Entries in each section are ordered from newest to oldest.
- Papers and Notes
- Tutorials, Surveys, and Slides
- Courses and Lectures
- Datasets
- Projects and Implementations
- Libraries and Tools
- Communities
- Contributing
Paper notes are organized with GitHub issue labels. Most existing notes are written in Chinese, but contributions in any language are welcome.
- 2023 Information Extraction and Open IE
- 2023 Named Entity Recognition
- 2023 Relation Extraction
- 2020 Named Entity Linking
- 2020 Knowledge Representation Learning and Knowledge Graph Embeddings
- 2020 Knowledge Graph Population and Construction — constructing knowledge graphs from different sources
- 2019 Knowledge-based Recommendation Systems
- 2019 Knowledge Base Completion and Knowledge Graph Reasoning — entity prediction and link prediction
- 2019 Ontology-based Information Extraction
- 2019 Semantic Role Labeling
Related NLP and machine learning tasks
- 2024 Recommendation
- 2023 Question Answering and Machine Comprehension
- 2023 Relational Reasoning
- 2021 Annotation
- 2021 Domain Adaptation and Domain-specific Learning
- 2020 Coreference Resolution
- 2019 Data Augmentation
- 2019 Dependency Parsing
- 2019 Natural Language Understanding
- 2019 Neural Machine Translation
- 2019 Slot Filling
- 2019 Summarization
- 2019 Text Classification
- 2023 BERT
- 2023 Embeddings and Pre-trained Models
- 2023 Multi-task and Joint Learning
- 2019 End-to-end Models
- 2019 Graph Neural Networks
- 2019 Transformer-based Models
- 2026 Awesome GraphRAG — actively maintained collection of GraphRAG surveys, papers, benchmarks, and open-source projects
- 2025 Ontotext Blog
- 2021 Recent Trends in Entity Linking
- 2018 Knowledge Extraction and Inference from Text — KDD tutorial: Part 1, Part 2
- 2018 Knowledge Graphs: The Power of Graph-based Search — Neo4j slides
- 2018 Mining Knowledge Graphs from Text — WSDM tutorial
- 2018 知识图谱论文合集 (Chinese)
- 2018 知识图谱入门(三) (Chinese)
- 2017 Enterprise Knowledge Graphs for Large Scale Analytics — IBM tutorial
- 2017 Getting Started with Knowledge Graphs — metaphacts slides
- 2016 Knowledge Integration in Practice — Yahoo slides
- 2020 A Survey on Knowledge Graphs: Representation, Acquisition and Applications — Shaoxiong Ji et al.
- 2019 Deep Learning in Knowledge Graph — notes
- 2018 Summary of Translation Models for Knowledge Graph Embeddings
- 2017 知识图谱研究进展 — 漆桂林等 (Chinese)
- 2016 知识图谱构建技术综述 — 刘峤等 (Chinese)
- 2016 知识图谱技术综述 — 徐增林等 (Chinese)
- 2014 垂直知识图谱构造工具与行业应用 — 阮彤 (Chinese)
- 2014 知识图谱:大数据语义链接的基石 — 李涓子 (Chinese)
- 2007 A Survey on Relation Extraction — CMU slides
- 2018 事件抽取与金融事件图谱构建 (Chinese)
- 2018 从零开始构建知识图谱 — Zhihu column (Chinese)
- 2021 Annotated Semantic Relationships Datasets (English)
- 2019 SemEval-2010 Task 8 — alternative implementation
- 2017 TACRED
- 2026 KG-Hub and KG-OBO — biomedical knowledge graph resources
- 2026 OpenKG.CN Datasets (Chinese)
- 2024 PheKnowLator — heterogeneous biomedical knowledge graphs and benchmarks
- 2026 GraphRAG-Bench — benchmark, datasets, and evaluation code for graph-based retrieval-augmented generation
- 2026 HippoRAG — knowledge graph and Personalized PageRank-based long-term memory framework for LLMs
- 2026 KAG — logical form-guided reasoning and retrieval framework for domain knowledge bases
- 2026 Knowledge Graph Builder — application for transforming documents and web content into a knowledge graph with LLMs
- 2026 LightRAG — graph-based retrieval-augmented generation framework with multiple storage backends and local deployment support
- 2020 KG-demo-for-movie — movie knowledge graph and KBQA; article (Chinese)
- 2020 Z_knowledge_graph — movie knowledge graph tutorial (Chinese)
- 2019 KGQA_HLM — Dream of the Red Chamber character graph and question answering system (Chinese)
- 2026 BioCypher — framework for creating and maintaining biomedical knowledge graphs
- 2026 PyKEEN — Python library for learning and evaluating knowledge graph embeddings
- 2024 GRAPE — Rust/Python library for graph representation learning and evaluation
- 2024 OpenKE — knowledge graph embedding framework
- 2022 cnSchema — open Chinese knowledge graph schema
- 2020 KnowledgeGraph — Chinese knowledge graph API
- 2017 DeepDive — system for extracting structured data from unstructured sources; homepage, papers
- 2026 Apache Jena — Java framework for Semantic Web and Linked Data applications
- 2026 Oxigraph — RDF and SPARQL toolkit and graph database with Rust, Python, and JavaScript interfaces
- 2026 RDFLib — Python library for working with RDF and SPARQL
- 2026 DeepKE — toolkit for entity, relation, attribute, and event extraction in knowledge graph construction
- 2026 doccano — text annotation tool
- 2025 HanLP — multilingual natural language processing library
- 2024 OpenNRE — neural relation extraction toolkit; related papers
- 2016 fact_triple_extraction — dependency parsing-based fact triple extraction (Chinese)
- 2025 InteractiveGraph — graph visualization tool
- 2025 Useful Tools and Lectures Related to Data Science (Chinese)
- 2026 OpenKG.CN — Chinese Open Knowledge Graph community
- 2016 Beijing Knowledge Graph Study Group (Chinese)
Contributions are welcome. Before opening a pull request, please make sure that:
- The resource is directly relevant to knowledge graph learning or engineering.
- The resource is publicly accessible and provides substantial educational or technical value.
- The link is stable and not duplicated elsewhere in the list.
- The entry includes a short, factual description and a language label when appropriate.
- The contribution does not primarily promote a paid product, commercial service, organization, or the contributor's own content.
- A pull request contains focused changes that are easy to review.
Commercial promotion, affiliate links, link farms, and low-content self-promotion will not be accepted. Maintainers may decline submissions at their discretion to keep the collection neutral and useful.
If you find a broken or outdated link, please open an issue or submit a pull request with a replacement.