VeritasGraph — open-source Knowledge Graph & GraphRAG framework on GitHub. Build multi-hop reasoning, ontology-aware retrieval, and verifiable attribution over your own data. Nodes, edges, RDF, linked-data — runs locally or in the cloud.

A machine learning tool for fishing entities

The Map Everyone's Missing: LLM Knowledge Engineering in 2026 — First unified guide connecting RAG, Context Engineering, Harness Engineering, Skill Systems, Agent Memory, MCP, and Progressive Disclosure

Building and Using Knowledge Graphs made easy

CLIPS programs I have completed for Expert Systems (Rule-Based AI)

Reduce hallucinations through first-principles reasoning, verification, self-critique, and explicit uncertainty for AI agents.

Practice #ontology engineering with Python (and other languages).

EMelodyGen creates emotional ABC melodies via templates. Rough4Q dataset is auto-labeled by small emotional datasets and music psychology to fine-tune backbone after augmentation with 99% correct rate, 91% emotional alignment and effective feature controls.|EMelodyGen通过模板控制ABC生成旋律情感。利用小型情感数据集和音乐心理学为Rough4Q数据集生成标签，经转换和增强后微调骨干网络。生成谱正确率99%，情感准确率为 91%。

Stanford Ontology 101 methodology for TypeScript domain modeling. 7-step process from competency questions to typed data architectures. Gruber 5 principles. 30+ concept mappings. Works with Claude Code, Cursor, Windsurf.

OMK — Observe. Measure. Know. Make every knowledge change in your AI application evidence-backed.

Knowledge engineering for AI agents: distill corpora too big for any context window into small, verified, git-native knowledge bundles

UniGraph——一站式知识图谱智造平台，支持领域建模、文档知识抽取、图谱构建与可视化，以及可追溯的 GraphRAG 问答。

Wikidata properties

John, an agent harness designed for building knowledge-dense applications.

A persistent AI operating system. 13 specialized agents + a runtime-portable 5-agent quality gate (Agent Council), 12 skills, 8 guardrails, 4 workflows. Built entirely from markdown files. Zero dependencies.

The Knowledge Engineering ENvironment for Timeline-based Planning

This project aims to create an ontology for a university using the Protege editor. The ontology defines various classes and their relationships within the university domain. It also includes queries and rules implemented in Protégé and CLIPS to retrieve information from the ontology.

Transition from copy-pasting to Knowledge Engineering. A manifesto and toolkit for AI in Academia.

🖥 DBpedia Visualization and Knowledge Engineering (DBpedia可视化与知识工程)

MASEO: A Multi-Agent System for Explainable Ontology generation