OntoAligner: A Comprehensive Modular and Robust Python Toolkit for...
Ontology Alignment (OA) is fundamental for achieving semantic interoperability across diverse knowledge systems. We present OntoAligner, a comprehensive, modular, and robust Python toolkit for...
Synalinks release 0.3 focuses on the Knowledge Graph layer
Your agents, multi-agent systems and LMs apps are still failing with basic logic? We got you covered.
Today we're excited to announce Synalinks 0.3 our Keras-based neuro-symbolic framework that bridges the gap between neural networks and symbolic reasoning.
Our latest release focuses entirely on the Knowledge Graph layer, delivering production-ready solutions for real-world applications:
- Fully constrained KG extraction powered by Pydantic: ensuring that relations connect to the correct entity types.
- Seamless integration with our Agents/Chain-of-Thought and Self-Critique modules.
- Automatic entity alignment with HSWN.
- KG extraction and retrieval optimizable with OPRO and RandomFewShot algorithms.
- 100% reliable Cypher query generation through logic-enhanced hybrid triplet retrieval (works with local models too!).
- We took extra care to avoid Cypher injection vulnerabilities (yes, we're looking at you, LangGraph 👀)
- The retriever don't need the graph schema, as it is included in the way we constrain the generation, avoiding context pollution (hence better accuracy).
- We also fixed Synalinks CLI for Windows users along with some minor bug fixes.
Our technology combine constrained structured output with in-context reinforcement learning, making enterprise-grade reasoning both highly efficient and cost-effective.
Currently supporting Neo4j with plans to expand to other graph databases. Built this initially for a client project, but the results were too good not to share with the community.
Want to add support for your preferred graph database? It's just one file to implement! Drop a comment and let's make it happen!
#AI #MachineLearning #KnowledgeGraphs #NeuralNetworks #Keras #Neo4j #AIAgents #TechInnovation #OpenSource
| 10 comments on LinkedIn
Want to explore the Anthropic Transformer-Circuit's as a queryable graph?
Want to explore the Anthropic Transformer-Circuit's as a queryable graph?
Wrote a script to import the graph json into Neo4j - code in Gist.
https://lnkd.in/eT4NjQgY
https://lnkd.in/e38TfQpF
Next step - write directly from the circuit-tracer library to the graph db.
https://lnkd.in/eVU_t6mS
Want to explore the Anthropic Transformer-Circuit's as a queryable graph?
Graph RAG open source stack to generate and visualize knowledge graphs
A serious knowledge graph effort is much more than a bit of Github, but customers and adventurous minds keep asking me if there is an easy to use (read: POC click-and-go solution) graph RAG open source stack they can use to generate knowledge graphs.
So, here is my list of projects I keep an eye on. Mind, there is nothing simple if you venture into graphs, despite all the claims and marketing. Things like graph machine learning, graph layout and distributed graph analytics is more than a bit of pip install.
The best solutions are hidden inside multi-nationals, custom made. Equity firms and investors sometimes ask me to evaluate innovations. It's amazing what talented people develop and never shows up in the news, or on Github.
TrustGraph - The Knowledge Platform for AI https://trustgraph.ai/ The only one with a distributed architecture and made for enterprise KG.
itext2kg - https://lnkd.in/e-eQbwV5 Clean and plain. Wrapped prompts done right.
Fast GraphRAG - https://lnkd.in/e7jZ9GZH Popular and with some basic visualization.
ZEP - https://lnkd.in/epxtKtCU Geared towards agentic memory.
Triplex - https://lnkd.in/eGV8FR56 LLM to extract triples.
GraphRAG Local with UI - https://lnkd.in/ePGeqqQE Another starting point for small KG efforts. Or to convince your investors.
GraphRAG visualizer - https://lnkd.in/ePuMmfkR Makes pretty pictures but not for drill-downs.
Neo4j's GraphRAG - https://lnkd.in/ex_A52RU A python package with a focus on getting data into Neo4j.
OpenSPG - https://lnkd.in/er4qUFJv Has a different take and more academic.
Microsoft GraphRAG - https://lnkd.in/e_a-mPum A classic but I don't think anyone is using this beyond experimentation.
yWorks - https://www.yworks.com If you are serious about interactive graph layout.
Ogma - https://lnkd.in/evwnJCBK If you are serious about graph data viz.
Orbifold Consulting - https://lnkd.in/e-Dqg4Zx If you are serious about your KG journey.
#GraphRAG #GraphViz #GraphMachineLearning #KnowledgeGraphs
graph RAG open source stack they can use to generate knowledge graphs.
SousLesensVocables is a set of tools developed to manage Thesaurus and Ontologies resources through SKOS , OWL and RDF standards and graph visualisation approaches
SousLesensVocables is a set of tools developed to manage Thesaurus and Ontologies resources through SKOS , OWL and RDF standards and graph visualisation approaches
The Dataverse Project: 750K FAIR Datasets and a Living Knowledge Graph
"I'm Ukrainian and I'm wearing a suit, so no complaints about me from the Oval Office" - that's the start of my lecture about building Artificial Intelligence with Croissant ML in the Dataverse data platform, for the Bio x AI Hackathon kick-off event in Berlin. https://lnkd.in/ePYHCfJt
* 750,000+ FAIR datasets across the world forcing the innovation of the whole data landscape.
* A knowledge graph with 50M+ triples.
* AI-ready metadata exports.
* Qdrant as a vector storage, Google Meta Mistral AI as LLM model providers.
* Adrian Gschwend Qlever as fastest triple store for Dataverse knowledge graphs
Multilingual, machine-readable, queryable scientific data at scale.
If you're interested, you can also apply for the 2-month #BioAgentHack online hackathon:
• $125K+ prizes
• Mentorship from Biotech and AI leaders
• Build alongside top open-science researchers & devs
More info: https://lnkd.in/eGhvaKdH
Building Flexible Virtual Knowledge Graphs with Ontop and Apache Iceberg | LinkedIn
What’s So Special About Apache Iceberg? Apache Iceberg is one of the most fascinating technologies when it comes to standardized access to large analytic tables. And Apache Iceberg combines very well with the idea of virtual knowledge graphs.
Nakala : from an RDF dataset to a query UI in minutes - SHACL automated generation and Sparnatural - Sparna Blog
Here is a usecase of an automated version of Sparnatural submitted as an example for Veronika Heimsbakk’s SHACL for the Practitioner upcoming book about the Shapes Constraint Language (SHACL). “ The Sparnatural knowledge graph explorer leverages SHACL specifications to drive a user interface (UI) that allows end users to easily discover the content of an RDF graph. What…
A zero-hallucination AI chatbot that answered over 10000 questions of students at the University of Chicago using GraphRAG
UChicago Genie is now open source! How we built a zero-hallucination AI chatbot that answered over 10000 questions of students at the University of… | 25 comments on LinkedIn
a zero-hallucination AI chatbot that answered over 10000 questions of students at the University of Chicago
Enhancing RAG-based apps by constructing and leveraging knowledge graphs with open-source LLMs
Graph Retrieval Augmented Generation (Graph RAG) is emerging as a powerful addition to traditional vector search retrieval methods. Graphs are great at repre...
We contributed recently to the "awesome semantic shapes" repository. This is a community-curated list of RDF shape resources, be it validators, generators…
We're excited to publicly release the Diffbot GraphRAG LLM! With larger and larger frontier LLMs, we realized that they would eventually hit a limit in terms… | 48 comments on LinkedIn
What if creating Linked Open Data was less like coding and more like writing? Could anyone extend the Semantic Web by sharing a document? Publish a knowledge… | 13 comments on LinkedIn
Building Knowledge Graphs with LLM Graph Transformer
🧱Building Knowledge Graphs with LLM Graph Transformer A deep dive into LangChain’s implementation of graph construction with LLMs If you want to try out… | 32 comments on LinkedIn
Building Knowledge Graphs with LLM Graph Transformer
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph…
SimGRAG is a novel method for knowledge graph driven RAG, transforms queries into graph patterns and aligns them with candidate subgraphs using a graph semantic distance metric
Using LLMs in each stage of building a Graph RAG chatbot: A case study
How we used Kùzu in combination with LLMs in multiple stages of the Graph RAG pipeline to build a QA chatbot for the Connected Data London Knowledge Graph Challenge
ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget
✨ Attention Information Extraction Enthusiasts ✨ I am excited to announce the release of our latest paper and model family, ReLiK, a cutting-edge… | 33 comments on LinkedIn
loading Microsoft Research GraphRAG data into Neo4j
Many people have asked about loading Microsoft Research #GraphRAG data into Neo4j. I wrote a quick notebook last night to import Documents, Chunks (TextUnit)… | 27 comments on LinkedIn
loading Microsoft Research hashtag#GraphRAG data into Neo4j
This notebook converts CSV data into a Neo4j Graph Database
This notebook converts CSV data into a Neo4j Graph Database. All you do is describe your data. Have you wanted to see what your data looked like as a graph…
FDR is a TypeScript library for building applications backed by an RDF model and the Semantic Web Technology Stack
Semantics friends and colleagues, Announcing the release of a new front-end application development library for RDF. Most of us have heard time and again how…
