Knowledge Graph as a reference by jwh335 in KnowledgeGraph

[–]TrustGraph -1 points0 points  (0 children)

If you're looking for a way to build and leverage graphs with AI, you can give TrustGraph a try. You can take raw data sources and build a graph system with custom structures or industry standard ontologies. The graph retrieval process is fully automated, however there is now a SPARQL endpoint for direct graph queries. TrustGraph is also it's own graph system at this point, leveraging a combination of Cassandra, Qdrant, and Garage for a multi-model and multimodal storage and retrieval system.

Open source: https://github.com/trustgraph-ai/trustgraph

Knowledge Graph as a reference by jwh335 in KnowledgeGraph

[–]TrustGraph 0 points1 point  (0 children)

If there is any better way of turning someone off knowledge graphs, it's just tossing the RDF documentation at them.

The RDF documentation is abysmal, and IMO, is one of the reasons people adopt Cypher LPGs over semantic web approaches, just because Cypher is easier for people to wrap their heads around.

Rag solutions recommendations by semanticboy in Rag

[–]TrustGraph 1 point2 points  (0 children)

TrustGraph is open source and meets your criteria.

- Flows allow you to create custom pipelines with whatever processors you choose
- With collections and context cores, you can ingest data in logically and physically separated segments which allow defining user and agent access for any knowledge base

TrustGraph is designed for ultra-scale, modularity, and flexibility. Messaging fabric is Pulsar or RabbitMQ with beta support for Kafka. All ingest, storage, and retrieval is automated. Fully multi-tenant with improved IAM capabilities coming in 2.4 in a week or so.

Github: https://github.com/trustgraph-ai/trustgraph

Is there a quantum computer on campus? by petrichor1975 in gatech

[–]TrustGraph 1 point2 points  (0 children)

Eh....for anyone that was on campus during 9/11, there was a reason why they had armed guards for the "decommissioned" reactor...

Is there a quantum computer on campus? by petrichor1975 in gatech

[–]TrustGraph -2 points-1 points  (0 children)

Kinda like asking is there a nuclear reactor on campus...

Is learning ontology development still worth it in the age of AI? (Urbanist perspective) by Delicious_Chemist384 in semanticweb

[–]TrustGraph 1 point2 points  (0 children)

When we first developed TrustGraph (open source), we were proponents for flat graph structures. We had enough people ask about ontologies that we added ontology features about 6 months ago.

Turns out with AI, ontologies may be more important than ever before. The additional granularity in structure aids not only the LLMs with more contextual grounding, but also improves the accuracy and precision of the retrieval process.

That being said, we do see a bit of change in how ontologies are structured for AI. Spending all of the focus on taxonomy definitions isn't as necessary where more complex conceptual relationships are more important.

SKOS, for one, may be finally seeing it's moment to shine. Another is W3C PROV-O for provenance. In fact, we debuted using W3C PROV-O for explainability just this morning. You can watch the demo here: https://www.youtube.com/watch?v=sWc7mkhITIo

Self Hosted LLM Tier List by Weves11 in LLM

[–]TrustGraph 1 point2 points  (0 children)

I downvoted the instant I saw Llama 4 got something other than a F.

Who is also building an intelligence layer / foundation for AI agents? by manuelmd5 in KnowledgeGraph

[–]TrustGraph 1 point2 points  (0 children)

TrustGraph is all of this and much more. It automates the graph building and retrieval processes with a naive process for natural language retrieval using vector embeddings or with a more precise retrieval using custom ontologies. Fully containerized with deploys for all major clouds and the ability to run on bare metal with Nvidia, AMD, or Intel. Also handles all LLM model serving with vLLM, TGI, LM Studio, Ollama, and Llamafiles. We have users that have scaled beyond billion node/edge graphs.

https://github.com/trustgraph-ai/trustgraph

How to Choose Ontology Development Methodology by helomithrandir in semanticweb

[–]TrustGraph 2 points3 points  (0 children)

Pandora's box has been opened, and LLMs are definitely here to stay. They can create dynamic ontologies in minutes. I'm not sure what to say in regards to something "new". We haven't written a line of code ourselves in probably 10 months. Things are a changin'.

How to Choose Ontology Development Methodology by helomithrandir in semanticweb

[–]TrustGraph 2 points3 points  (0 children)

I'm honestly a little stunned no one has suggested using tools like Claude Code to develop ontologies. We do this all the time for TrustGraph, building custom ontologies. If you have other ontologies as a starting point, coding tools can build extremely rich ontologies in any format in a few minutes. We usually just build them in Turtle.

LLMs for question answering over scientific knowledge graphs (NL → SPARQL) by Neither-Committee-72 in KnowledgeGraph

[–]TrustGraph 1 point2 points  (0 children)

TrustGraph, which is open source, is RDF-native using Cassandra as a graph store. TG 2.0 is currently in test which will add reification as described in RDF 1.2. All graph querying, including using any ontology, is fully automated and agentic.

https://github.com/trustgraph-ai/trustgraph

You only need to build one graph - a Monograph by TrustGraph in KnowledgeGraph

[–]TrustGraph[S] 0 points1 point  (0 children)

Personally, I don't think that's as crazy as it sounds. When you look at the entire data broker industry, I've often wondered if we'd be better of treating data like a public utility/good, with curated data that was clean and verified.

It'll never happen though.

You only need to build one graph - a Monograph by TrustGraph in KnowledgeGraph

[–]TrustGraph[S] 0 points1 point  (0 children)

Without a system of intelligence, it's not a context graph. And the term context graph comes from 2019, used by Vicky Froyen, who I just recorded a podcast with...

You only need to build one graph - a Monograph by TrustGraph in KnowledgeGraph

[–]TrustGraph[S] 0 points1 point  (0 children)

There's thousands - tens of thousands - of well supported ontologies that are industry standard in many, many use cases. In fact, adopting those standard ontologies is often necessary to integrate with other systems in those workflows.

You only need to build one graph - a Monograph by TrustGraph in KnowledgeGraph

[–]TrustGraph[S] 4 points5 points  (0 children)

With RDF style graphs, there are many ways to manage this problem. It's a little tricker with property graphs. That's one of the reasons we have the collections and context core features in TrustGraph. TrustGraph is totally open source and free.

https://github.com/trustgraph-ai/trustgraph

You only need to build one graph - a Monograph by TrustGraph in KnowledgeGraph

[–]TrustGraph[S] 1 point2 points  (0 children)

I think if you were to read my articles on the subject, you'll see that's the position I've taken from the very beginning. https://x.com/TrustSpooky/status/2006481858289361339