We build KGs the way nature builds matter
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Updated
Apr 30, 2026 - Python
We build KGs the way nature builds matter
Some papers on Temporal Knowledge Graph Embedding and Reasoning
[WSDM 2022] EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs
The official repo of TimeLlama, an instruction-finetuned Llama2 series that improve complex temporal reasoning ability.
[WWW 2023] The source code of "Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning"
Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
ChronoKGE - A knowledge graph embedding framework for time-focused representation learning (RepL4NLP @ ACL 2022)
Open-source, multi-provider research automation with persistent experts, eval-based routing, and cost guardrails.
EMNLP 2018: HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding
Temporiki — Lightweight temporal Context Graph + Obsidian-native LLM Wiki with real memory (SQLite + Chroma). Zero-command daily flow.
Code for https://arxiv.org/abs/1907.03143
Zero-install persistent memory brain for Claude Code and Claude Desktop. Stops re-asking and re-deriving across sessions. SQLite FTS5 default, ChromaDB + Ollama on the semantic branch.
A centralized, production-ready ecosystem of advanced OpenClaw AI Agent Skills. Built by El Moorish, this repository features Zero-Trust Context Management architectures (Temporal Knowledge Graph Synthesizers and Cognitive State Compaction) alongside upcoming capabilities for Real Estate market profiling and Educational AI Tutoring.
MindGraph OS: An AI powered knowledge operating system that transforms documents and codebases into a living temporal knowledge graph with autonomous reasoning agents.
⏳ CHRONOS — Autonomous Data Incident Root Cause Analysis Agent. Triple-graph architecture (OpenMetadata + Graphiti + GitNexus) powered by LangGraph. Travels through metadata time to find where data quality broke.
Provide persistent memory for LLM runtimes, agents, and IDEs with zero installation.
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