Re: Foundations for a Large Graph Model

Dear Sebastian,

Knowledge graphs are the number one priority for all manner of knowledge
representation and mathematical frameworks for empirical analysis,  not
just AI.

Milton Ponson
Rainbow Warriors Core Foundation
CIAMSD Institute-ICT4D Program
+2977459312
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean

On Fri, Mar 20, 2026, 12:40 Sebastian Samaruga <ssamarug@gmail.com> wrote:

> Hi everybody. Let me reshape my original post. It was a mess. Let's start
> sharing some context to the discussion:
>
> "Gartner just made Knowledge Graphs the number 1 infrastructure priority
> for enterprise agentic systems"
>
> https://share.google/aimode/m7XZVTIYCnyWMLefG
>
>
> https://www.linkedin.com/posts/amyhodler_graph-chat-neo4js-philip-rathle-on-neuro-symbolic-activity-7432506087985291265-rfB7
>
> And an FCA attempt to render Large Graph Models. Maybe adding some little
> algebraic semantics into embeddings could be of any help.
>
> ---
>
> Foundations for a Large Graph Model:
>
> FCA (Formal Concept Analysis):
> FCA Contexts: Objects x Attributes matrix.
>
> Context triples encoding:
> ContextPoint : (context : ContextPoint, object : ContextPoint, attribute :
> ContextPoint);
>
> ContextPoint class:
> - uri : String
> - primeID : long
> - context : ContextPoint
> - object : ContextPoint
> - attribute : ContextPoint
> - contextOccurrences : Set<ContextPoint>
> - objectOccurrences : Set<ContextPoint>
> - attributeOccurrences : Set<ContextPoint>
> + getContext
> + getObject
> + getAttribute
> + getContexts
> + getObjects
> + getAttributes
> + getPrimeIDEmbedding
>
> Occurrence Monad: ContextPoint (Context, Object, Attribute Occurrences)
> wrapper / filter / traversal streams reactive composition / activation.
>
> Render SPO Graphs into FCA Contexts from input triples:
> Each S, P, O from input triples with Contexts of their own. Example:
> Predicate Context, Subject Objects, Object Attributes (P, S, O). "Rotated"
> SPO Contexts.
>
> (S, P, O) Context;
> (P, S, O) Context;
> (O, P, S) Context;
>
> Prime ID Embeddings:
>
> Each ContextPoint (singleton for a given URI) is assigned an unique
> incremental Prime Number Identifier.
>
> For a given ContextPoint occurrences in a given Context its Prime ID
> Embedding is calculated as the product of this occurrence Prime ID with the
> Prime ID Embeddings of the other two parts of the occurrences.
>
> For example: given an object in a given context its Prime ID Embedding is
> the product of its Prime ID (Embedding) by the Prime ID (Embedding) of the
> occurrence context by the Prime ID (Embeddings) of this object's attributes
>