AI Knowledge Graph
å€éšAI Knowledge Graph transforms unstructured text into interactive knowledge graphs powered by any OpenAI-compatible LLM. It automates the extraction of subject-predicate-object triples, entity standardization, relationship inference, and generates explorable HTML visualizations with features like community colors, centrality-based sizing, and pan/zoom controls. Ideal for researchers, analysts, and developers seeking to uncover insights from research papers, books, or reports, this tool accelerates knowledge discovery while highlighting potential LLM inaccuracies for review.
説æ
AI Knowledge Graph transforms unstructured text into interactive knowledge graphs powered by any OpenAI-compatible LLM. It automates the extraction of subject-predicate-object triples, entity standardization, relationship inference, and generates explorable HTML visualizations with features like community colors, centrality-based sizing, and pan/zoom controls. Ideal for researchers, analysts, and developers seeking to uncover insights from research papers, books, or reports, this tool accelerates knowledge discovery while highlighting potential LLM inaccuracies for review.
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- Converts unstructured text to SPO triples using OpenAI-compatible LLMs
- Supports local LLMs like Ollama via config.toml
- Performs text chunking with overlap
- Entity standardization for aliases
- Rule-based and LLM-assisted relationship inference
- Generates interactive PyVis HTML knowledge graphs
äž»ãªçšé
- 1.Extracting insights from research papers and reports
- 2.Visualizing relationships in history books or narratives
- 3.Prototyping knowledge graphs for biomedicine or scientific documents
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- Researchers and developers analyzing unstructured English text documents
- Prototypers in biomedicine or science needing quick KG visualizations
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- Users needing production-ready KG querying or API access
- Processors of non-English content like Chinese
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- Interactive HTML visualization with color-coded communities, node centrality sizing, solid/dashed edges
- Configurable pipeline via config.toml (LLM settings, chunking, standardization, inference)
- CLI with options like --input, --output, --test, --no-standardize
- Outputs raw JSON data alongside HTML graph
- Light/dark mode, filters, pan/zoom
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- 1.9k GitHub stars and 271 forks showing strong community interest
- Easy installation and quick CLI start for non-experts
- High-quality interactive visualizations accelerating insights
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- Relies on LLM accuracy, prone to hallucinations requiring user review
- Limited community feedback with potential early-stage bugs
- No built-in chat or query interface over the knowledge graph