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This repository contains the implementation of AutoSchemaKG, a novel framework for automatic knowledge graph construction that combines schema generation via conceptualization.
| Date | Stars |
|---|---|
| 2026-07-31 | 790 |
| 2026-08-01 | 790 |
| 2026-08-06 | 790 |
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# AutoSchemaKG: A Knowledge Graph Construction Framework with Schema Generation and Knowledge Graph Completion This repository contains the implementation of AutoSchemaKG, a novel framework for automatic knowledge graph construction that combines schema generation via conceptualization. The framework is designed to address the challenges of constructing high-quality knowledge graphs from unstructured text. Homepage and Documentation: https://hkust-knowcomp.github.io/AutoSchemaKG/ This project uses the following paper and data: * **Paper:** [Read the paper](https://arxiv.org/abs/2505.23628) * **Full Data:** [Download the dataset](https://huggingface.co/datasets/gzone0111/AutoSchemaKG/tree/main) (huggingface dataset) * **Neo4j CSV Dumps:** [Download the dataset](https://huggingface.co/datasets/AlexFanWei/AutoSchemaKG) (huggingface dataset) ### Update - (05/12) Add Documentation for atlas-rag package and example directory. Include quick start examples for knowledge graph construction, hosting, and multi-hop QA evaluation. - (05/07) Update with batch generation and refactor the codebase. Add comprehensive documentation for examples including PDF/Markdown conversion, multi-language processing, parallel generation, and custom extraction. - (24/06) Add: ToG, Chinese KG construction (refer to example/multilingual_processing.md for KG construction with different languages). Separate NV-embed-v2 transformers dependency. ## AutoSchemaKG Overview AutoSchemaKG introduces a two-stage approach: 1. **Knowledge Graph Triple Extraction**: Extract triples comprising entities and events from text by using LLMs 2. **Schema Induction**: Automatically generate schema for the knowledge graph by using conceptualization and create semantic bridges between seemingly disparate information to enable zero-shot inferencing across domains The framework achieves state-of-the-art performance on multiple benchmarks and demonstrates strong generalization capabilities across different domains. ## ATLAS Knowledge Graphs ATLAS (Automated Triple Linking And Schema induction) is a family of knowledge graphs created through the AutoSchemaKG framework, which enables fully autonomous knowledge graph construction without predefined schemas. Here's a summary of what ATLAS is and how it works: ### Key Features of ATLAS Knowledge Graphs - **Scale**: Consists of 900+ million nodes connected by 5.9 billion edges - **Autonomous Construction**: Built without predefined schemas or manual intervention - **Three Variants**: ATLAS-Wiki (from Wikipedia), ATLAS-Pes2o (from academic papers), and ATLAS-CC (from Common Crawl) ## Project Structure ``` AutoSchemaKG/ ├── atlas_rag/ # Main package directory │ ├── kg_construction/ # Knowledge graph construction modules │ ├── llm_generator/ # Components for large language model generation │ ├── retriever/ # Retrieval components for RAG │ ├── utils/ # Utility functions for various tasks │ └── vectorstore/ # Components for managing vector storage and embeddings ├── example/ # Comprehensive examples and tutorials │ ├── atlas_billion_kg_usage.ipynb # Using ATLAS billion-scale KGs │ ├── atlas_full_pipeline.ipynb # Complete KG construction pipeline │ ├── atlas_multihopqa.ipynb # Multi-hop QA evaluation │ ├── example_data/ # Sample datasets (JSON, Markdown, PDF) │ ├── example_scripts/ # Production-ready scripts │ │ ├── benchmark_extraction_example/ # Time cost benchmarking │ │ ├── custom_extraction/ # Custom prompts and schemas │ │ ├── neo4j_kg/ # Neo4j API hosting │ │ └── parallel_generation/ # Large-scale parallel processing │ ├── generated/ # Output directory for generated KGs │ ├── hotpotqa_corpus_kg_input/ # Benchmark extraction results │ ├── pdf_md_conversion/
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2c530c0c2dac1350, topic:rag, topic:knowledge-graph, desc:knowledge graph