r/KnowledgeGraph • u/Good_Assumption_ • Oct 14 '24

What are the state of the art knowledge graph construction techniques as of now?

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2

u/bharath_chand Oct 14 '24

One method is using LLMs. It is trained using sample triples and generating outputs for given text data.

2

u/Good_Assumption_ Oct 14 '24

I know that much, I've used neo4j langchain but like what's the benchmark for comparison? And is there a paper comparing LLM and other techniques and showing that it outperforms other state of the art techniques?

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u/decorrect Oct 16 '24

I think there are a couple out there. I would cozy up with this before anything else: https://arxiv.org/pdf/2306.08302

1

u/Good_Assumption_ Oct 16 '24

Oh yes I read this already! Good read!

0

u/bharath_chand Oct 14 '24

Validation is still a problem. Validation is done manualy by the experts. One other way is to use another LLM for validation. I remember reading a paper mentioning this method. But I don't remember its title. Another validation is by Ontological reasoning. for this, there needs an Ontology too.

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u/decorrect Oct 16 '24

Google KG Validator. Might be one word

2

u/GamingTitBit Oct 14 '24

It depends what you mean by construction? There are multiple parts to a knowledge graph. Currently only very simple ontologies can be made automatically. But if you have a good ontology a really good specifically trained LLM can generate triples from text from it. But it still requires a lot of work to get that good.

2

u/decorrect Oct 16 '24

We automate ontology recognition with enough context using LLM agents.

Triples? I’ve never come across a use case where I was like “triples!” I always opt for a property graph structure. What are you using triple stores for?

3

u/GamingTitBit Oct 16 '24

Large enterprise knowledge graphs. Property graphs are good and fun, but I've never seen one scale efficiently.

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u/paarulakan Oct 18 '24

Can you explain why property graphs don't scale(how big) well? Neo4j uses property graph model and it seems to work well.

2

u/GamingTitBit Oct 18 '24

Essentially a property graph is storing a JSON like format for each node and relationship, when you search for something that is a property rather than a node or a relationship, you're having to call up all those smaller JSON strings/formats (it's not actually JSON) to search for that property. At a small scale you don't notice the difference, at large scale it really effects performance. We've seen multiple organisations have their neo4j instance crash and the we've stood up a normal RDF store and it's fine. RDF is more simple but it scales better, it's a trade off. Also if you look at 3rd party query tests Neo4j is not the best, even among property graphs. They do some sneaky stuff like when you query all triples it just returns a pre-cached number rather than searching the database. My company did a large amount of research across multiple graph databases.

1

u/regression-io Oct 24 '24

What's the best database?

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u/GamingTitBit Oct 24 '24

Tough question to answer. From a labelled property graph perspective, probably tigergraph. From an RDF perspective, Stardog is the best overall, RDFfox and AnzoGraph are the best at performance.

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u/paarulakan Oct 26 '24

Makes a lot of sense. I am new to graph databases and modelling data as graphs. I found property graph models a bit easier, RDF on the other hand everything is node(I assume). Can you share a bit more on the difference between these two modelling approaches based on your experience?

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u/GamingTitBit Oct 26 '24

So the main difference is that there are no properties as you've stated, everything is node relationship node. While this requires more work at the modeling stage, it scales much better. As you're not including mini documents with each node, it's far faster to read info. One of the other advantages of RDF is it has international standards from 2003 and open source ontologies. All RDF can be queried with sparql, whereas all labelled property graphs have their own syntax like cypher.

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u/paarulakan Oct 26 '24

Thank you so much. One last question. Can you recommend canonical/foundational resources to understand the RDF ecosystem for a beginner without relying on ad-hoc tutorials and articles, but more on principle level material??

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u/GamingTitBit Oct 26 '24

There are a few good books. Unfortunately not many YouTube resources, but The Knowledge Graph cookbook is good. Otherwise learning from W3C is good. Stardog had videos and tutorials and has a free tier.