GraphNews

Examples of KG + RAG & Schemas that are used by various systems across different domains, for inspirational purposes.

An Overview of Knowledge Graph Embeddings (KGEs) – Part 1. 🧠🍄 Knowledge Graphs represent real-world facts as structured data. Nodes represent entities or…

We switched from building simple LLM agents to graph-based AI solutions this year. In our experience, agentic graphs are the only way to 1) ensure high… | 44 comments on LinkedIn

There is a lot of noise about #KnowledgeGraphs for LLM apps. But we haven't seen an enterprise-grade implementation. This approach could be one. "The… | 11 comments on LinkedIn

How exactly do knowledge graphs work? Before you dive deep into GraphRAG, learn the basics of property graphs - each node and relation can store a structured…

AI Reasoning on Cybersecurity RDF Graphs https://lnkd.in/dAKb43bV Allen Woods, Tony Seale, Andrey Prozorov, Andy Watkin-Child CSyP, CEng, MSyI, MIMechE… | 10 comments on LinkedIn

This is something very cool! 3. GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models "GraphReader addresses the…

Discover why GraphRAG will subsume vector-only RAG and emerge as the default RAG architecture for most use cases.

Interactive Network Graphs for Uncovering Complex Multicollinearity 🕸️ Visualize multicollinearity in large datasets with interactive network graphs using… | 18 comments on LinkedIn

See how to combine structured and unstructured semantic queries and to use large language models to orchestrate question answering over a knowledge graph.

This weekend we released a first version of JSON-LD Framing of DFRNT hypergraphs, that is now exposed as a user interface. This is great for technical…

Recently, Microsoft announced with a post their GraphRAG offering. This article provides a brief overview of their approach, how it compares to other Graph RAG varieties, what problems it can address and what it cannot.

Knowledge graphs (KGs) are a specific type of #data structure designed to represent entities and the connections between them. They move beyond simply storing… | 14 comments on LinkedIn

Combine text extraction, network analysis, and LLM prompting and summarization for improved RAG accuracy

The Programmable Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected - SynaLinks/HybridAGI

Ask your (research) question against 76 Million scientific articles: https://ask.orkg.org Open Research Knowledge Graph (ORKG) ASK (Assistant for Scientific…

Copyright 2024 Kurt Cagle / The Cagle Report Recently, I've spent a lot of time talking with clients about the need for knowledge graphs in LLMs, why they are not "graphlike," and why we may need to rethink the whole transformer model. I think this topic is worth exploring, and I'd like to have a po

Predicting the architecture of intelligent organizations

Our paper "Are Large Language Models a Good Replacement of Taxonomies?" was just accepted to VLDB'2024! This finished our last stroke of study on how knowledgeable LLMs are and confirmed our recommendation for the next generation of KGs. How knowledgeable are LLMs? 1.

Zazuko Blueprint is an enterprise knowledge graph frontend and browser, designed to make RDF Knowledge Graphs accessible and customizable for domain users. - zazuko/blueprint

Can LLMs understand graphs? The results might surprise you. Graphs are everywhere, from social networks to biological pathways. As AI systems become more…

From SQL to GQL, the new graph query language standard and a pivotal development for advancing data analytics in the era of GenAI and beyond.

PDF | BIFROST is a novel query engine for graph databases that supports high-fidelity data modeling on arbitrary and evolving graph topologies. It... | Find, read and cite all the research you need on ResearchGate

What Could Go Wrong When We Start Using LLMs to Organize Knowledge? 7 Pain Points of GraphRAG Alright, tech enthusiasts and AI aficionados. We need to discuss… | 43 comments on LinkedIn

Generalist and Lightweight Model for Relation Extraction (Extract any relationship types from text) - jackboyla/GLiREL

Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies.

It was recorded and I hope it'll get… — Emil Eifrem (@emileifrem)

Every time I write about why graph-based RAG produces more insightful and more accurate answers for Q&A / digital assistant AI applications, people ask — do… | 21 comments on LinkedIn

If you, like me, aspire to create your knowledge graph on Google, I have two recommendations for you: 1º Use the tool at demo.nl.diffbot.com to visualize the…