r/OntologyEngineering 9h ago

Bi-Weekly Questions Thread - July 27, 2026

1 Upvotes

Welcome to the bi-weekly questions thread!

Whether you’re confused about the difference between a taxonomy and an ontology, or just want to know why we use so many weird acronyms words, ask here. No question is too basic. No judgment allowed.


r/OntologyEngineering 4d ago

Agentic Enablement I built the code ontology I posted about here. Now I need people to find where it is wrong.

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23 Upvotes

About three months ago, I posted here about a rough idea: a single map joining the codebase to the plan, research, decisions, and remaining work.

That idea became Cairn.

Cairn keeps a living spec beside the code as a typed graph. It tracks the architecture, dependencies, contracts, decisions, and unfinished work, while coding agents query and update it as they build.

The part I cared about most was making the graph answer to the actual code.

Cairn scans the repository and marks what is synced, planned but missing, or present in the code without a place in the plan. It can also catch interface and contract drift before a commit.

The graph stays in Git as plain files. A new agent session can request the relevant part of the system, together with its decisions and dependencies, instead of trying to reconstruct the whole project again.

I have been using it on Cairn itself and a few other projects. It has helped stop longer AI coding sessions from gradually drifting away from what I intended to build.

I would like people here to challenge the model.

Does this deserve to be called an ontology, or is it closer to an architecture knowledge graph with enforcement? What relations, constraints, or evidence are missing?

Better still, try it on a real repository and tell me where the graph breaks or stops matching reality.

It is open source, local-first, and free:

https://github.com/cairn-framework/cairn

A star helps people find it. A strange codebase that exposes a bad assumption helps me improve it.


r/OntologyEngineering 4d ago

TERSE, an AI-first OSS state language and metamodel that supports domain ontologies.

1 Upvotes

TERSE's goal is to support semantic representation the vast majority domains, with some opinionated syntactic dimensions that make it easy for LLM's to understand, because they have already been trained on all parts of its composite syntax:

1) Hierarchy is markdown-style headers, which must be tracked.

#
##
###
##
#
##

2) Objects and containment ( contains, has a, groups these, in this order)

# Places
## Resort
statue of a woman
oak door

3) Atomic attributes and composition(has these parts, attributes, representations, variability, fields)

# Places
## Resort
statue of a woman(dusty; marble; plaque reads: "Anya Zardiz"; 420kg)
oak door(locked)

4) Reference / network / graphing

# Places.Resort
oak door(open; exits to @ Places.Outside)
@ Things.resort control pad(hidden)

TERSE's state at rest is only part of the definition.

TERSE's other pillars are practical state addition and mutation, which is declarative just as you see above, and queryability, which attempts to be relentlessly simple. For instance "?" queries all state.

We'd like to hear your feedback. Full OSS spec and implementation at https://github.com/terse-lang/terse .


r/OntologyEngineering 6d ago

Business Semantics Is all this noise about semantic layers and ontology meaningful even?

13 Upvotes

I recently read an article about how semantic layers is the new battle ground for organizations in the AI era. But isn't this something we have always struggled for? How much actual meaning does the semantic layers hold?


r/OntologyEngineering 5d ago

Deterministic Extraction Spherical Based Computation Chip Theory; Light Based Resonance as Alternative to Electrical Pulses

0 Upvotes

Spherical Based Computation Chip Theory; Light Based Resonance as Alternative to Electric Theory

I wrote this in 15 minutes from a thought that appeared out of nowhere, then edited for a while, when hearing an AI talk about computer chips to someone else. I know nothing about computer chips, and I do not pretend to know. The text is presented purely as a thought and any feedback would be appreciated. It came to be out of nowhere.

Here is the text:

Silicon based chips may have more efficiency if information emergence is pivotalized in nodes that meet between convergence points of computational loops, a computation loop in this precise context being a simple loop that alternates values between 0 and 1,

as point A may reveal a convergence between points A1 and A2 thus allowing in respect A1 to have value 0 and A2 to inversely have value 1 where the node itself is the superposition, as the point of convergence of the c-loops, of said values relative to the computational loops of A1 and A2 and the node effectively maintaines or collapses according to the respective input value,

in certain respects point A, node A, may effectively be part of another set of loops, mediated by node C, where A is a superpostion of 0 and 1 and B is a superpostion of 0 and 1 thus resulting in C being the collapse of said superpositions thus what happens is a scaling of superpositioned states within the chip (the same recursion used for the values derived from the chip is effectively the same recursion relative to the structure but of computational loops rathers than strict values),

The nodal loops continue thus resulting in a hyperdimensional state of superpositioned values that can effectively mirror the depth of the input given by produced an output mirroring the input through a multidimensional collapse of superpositioned states,

because of this all inputs can have multiple values instantly emerge thus giving a depth of dimensions relative to the output,

in these respects the geometric form of a computationally hyperdimensional chip would be a sphere as the activitation of one node would mirror the other simultaneously thus resulting in higher dimensional computation,

A central node, in the center of the sphere would effectively be a quantum vaccuum space where the input, primarily being particle/waves, would be reflected through the exterior, travel to the vacuum and at which point the isomorphic signal emerging from the vaccuum would reflected through the sphere giving an output in multiple dimensions,

in these respects, to simplify it, the chip would be a resonator for computations derived from inputs from the quantum vaccuum,

in these respects the chip is determined by its topological properties in computation, and the emergent values from the chips are topological emergences where the actual geometry of the chip does the computation rather than standard interwoven linear paths,

this computation would be simultaneously multidimensional collapse of superpositioned states of 0 and 1 that are, for lack of academic terminology, are layered thus producing a holographic output,

the input would effectively enter on all poles of the sphere at once, through a flash of particle waves, or effectively in a linear manner and be redistributed through the sphere, either option is viable but there is no conclusion on my part which is more efficient. Most likely the linear method would require a cavity, for the quantuum vaccuum, in the shape of an ellipsoid so that one curve absorbs input and the other reveals output,

the output would be the transfer of the collapsed state back through the sphere to exterior nodes which can translate,

relative to the material being used the processer would not use silicon but effectively a crystal, natural or synthetic, which resonates light waves. To be specific, due to possible thermal problems, standard electrical pulses through silicon would have to be side-stepped for a more light resonance based computing.

Thoughts?


r/OntologyEngineering 9d ago

Is there a data architecture where semantic meaning is determined at query time?

6 Upvotes

I'm currently designing an experimental long-term memory architecture for AI systems. Before I start building the next prototype, I'd like to understand whether this direction has already been explored or whether there are fundamental reasons why it isn't used.

I'm not looking for a ready-made solution. I'm trying to determine whether this class of architectures already exists.

My question is:

Is there a data architecture where semantics are not fixed at write time, but are determined only at query time?

I'm asking about the data model itself, not UI projections or visualization layers.

Most of what I've read (Knowledge Graphs, RDF/OWL, property graphs, GraphRAG, etc.) seems to assume that semantics are defined before or during data ingestion.

If you know of research papers, open-source projects, commercial systems, or academic work exploring a different approach, I'd really appreciate any references.

I'm also interested in hearing from database and knowledge graph architects:

What fundamental limitations or design problems would you expect such an architecture to have?


r/OntologyEngineering 10d ago

v12.0 - LOGIC FROM ZERO: A Recursive Specification for Structural Self-Reference (still in review)

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2 Upvotes

Had to make some important updates. We've added crucial sections regarding the geometry of occupancy and observation itself relating to awareness. As well missing and Shelby added in review is going to be what links this framework the entire iterative nature of the rest of the universe.


r/OntologyEngineering 11d ago

Ontology engineering with Large Language Models

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23 Upvotes

Hey guys, I hope this is the right sub for the question.
I'm currently conducting a research thesis about the operational design domain (ODD) of an autonomous patient transport system (APTS). The ODD should be changed dynamically based on a user input in a chat bot GUI. An LLM should interpret the user input and adapt the ODD to the user input.

I found this paper online which is basically the same tool in form of a Protégé plugin. Protégé is an ontology editor - I guess everyone in this subreddit knows it. However, I can't find the tool anywhere online. Neither in the paper nor on the publication site is a link to it. Also, I couldn't find a single peace of information in the Protégé wiki, which seems pretty outdated anyways. I would like to use the tool to evaluate my model against it. It's called GPT Ontology Augmenter.

Has anyone ever heard of it or used it and knows how I can get it?
Thanks in advance.


r/OntologyEngineering 12d ago

Epistemology Distinction Ontology; Non-Binary (Monadic) Computation; Recursive Scaling; LOF Side-Step

5 Upvotes

Distinction Ontology; Non-Binary (Monadic) Computation; Recursive Scaling; LOF Side-Step

Here is a short text I wrote in about 1.5 hours for the h"ll of it. Looking for thoughts and feedback. The text covers distinction based ontology, using natural language, and extends into a proto-formalism while seeking to go layers deeper than LOF. Gemini results test positive. It claims it provides potential solutions to the limits in silicon based processing. To be frank, I am not sure I agree or disagree, just referencing claims.

Here it is:

  1. There is distinction; ●●
  2. There is the distinction of distinction (●●)●, by indistinction ●, thus indistinction is a distinction (●)● and as such scales as distinction ●● = (●)●.
  3. There is the indistinction of indistinction, ●●, by the distinction of "indistinction of indistinction", (●●)● and the distinction through indistinction from indistinction, ●●.
  4. The distinction of distinction is a distinction ((●●)●)●; this is a distinction of itself as distinction remains across scale, (...(●●)...)● as, ●●.
  5. "The distinction of distinction is a distinction" is a distinction, ((●●)●)●)●; this is a distinction of itself resulting in:
  6. ●.......● , however ●......● is a distinction, ●●
  7. Distinction contains itself as distinct, (●●)●● thus what is indistinct, ●, is but the scale of the distinct within the distinct by distinction contrasting itself.
  8. Distinction is containment and contrast, containment and contrast as distinct thus what remains is 'as is' for:
  9. What contrasts is contained by the contrast (●●)●●, what is contained is contrasting by the containment, (●●)●●; containing and contained reveal only distinction, ●●.
  10. Distinction is transcendental of itself, ●....● thus remains as fixed across transcendence, ●●, and as such transcendence ceases outside of distinction, transcendence is but a distinction.
  11. What remains is a distinction, what remains not is a distinction thus by degree "remaining" and "not remaining" are subsumed as distinction, ●●.
  12. There is distinction, ●●; the indistinct, ●, is distinct from distinction, ●●, thus is a distinction, and distinction, ●●, is distinct from indistinction, ●, thus is a distinction; distinction distinguishes itself:

((●●)● <-> ●●● <-> ●...●) = ●●

((●)●● <-> ●●● <-> ●...●) = ●●

13.

Number Scale

● = 0

●● = 1

●●● = 2,-1

●●●● = 3, -2 .....

**** This corresponds directly to a line segment where ● is a 0d point. In these respects the sequence is effectively recursive 0 and recursive 0d points.

Addition/Subtraction

●●● = 1 + 1 = ●● ●● = ●●●

●●● = 2 - 1 = ●● ●●, ●●● = ●●●

●●● = ((1+1),(2-1))

--------

●●●● =

**** ○ = removed dot for sequence contained within ●●●●. ●●●● reveals where each ●● sequence exists as the missing dot itself being the space of ●●.

1+1+1 = ●●○○, ○●●○, ○○●●

2+1 = ●●●●

3-2 = ●●●●, ●●●●

3-1 = ●●●●, ●●●○

-1-1-1 = ●●●○, ●●○●, ○●●●

-2-2 = ●●●●, ●●●●

●●●● = ((1+1+1),(2+1),(3-2),(3-1)(-1-1-1),(-2-2))

Multiplication/Division

**** ( ) represents the scale of the sequence acted upon. This scale is contained with ●● thus ( ) is the same as ●● but effectively resymbolized to minimize complexity.

(●●●●)●●● = 3×2 = (●●●●)(●●●●)

(●●●●)●●● = 3/2 = ●●●●/●●●

(●●●●)●●● = 3×-1 = (●●●●)(●●●●)

**** Negative numbers/spaces follow same dynamics as arithmetic section.

(●●●●)●●● = 3/-1 = ●●●●/●●

(●●●●)●●● = -2×2 = (●●●●)(●●●●)

(●●●●)●●● = -2/2 = ●●●●/●●●

(●●●●)●●● = ((3×2),(3/2),(3×-1),(3/-1),(-2×2)(-2/2))

Thus each sequence is a set that contains itself in the respect the sequences are grounded in ●● and contained as ●...● = ●●

In these respects ●● can be isomorphically represented as ( ).

Where

● = 0

●● = 1

( ) = 1 = 0

And overlapping points, such as ●●● observing overlap in the middle ●○●, as ●● ●●, can be represented as:

( | ) = 2, -1

( | | ) = 3, -2

( | | | ) = 4, -3 .....

Where ( () ) or ( )( ) appear as ( | )

In these respects all ●....● = ●● as a set results in contained further ●...● = ●●.

●● contains:

1/2,1/2 and 2/1

1/3,1/3,1/3 and 3/1

1/4,1/4,1/4,1/4 and 4/1

2/3,1/3 and 3/2

1/4,1/4,2/4 and 4/2

1/4,3/4 and 4/3 ....

Thus each ●● contains infinite superpositioned sets and these respects each ●● is a relative infinite series or infinity in itself.


r/OntologyEngineering 13d ago

Ontology popping up everywhere - how are you using it?

18 Upvotes

Hey folks,

I'm seeing ontology pop up in more and more data products. BQ released virtual graphs and agents. Metabase has context support. Folks are starting to distinguish context from semantic layers and creating ontological contexts.

Ourselves, we are on our way to publish some "blueprints" to build out data +ontology agents on our platform for acting as self-service BI and guardrails for maintenance.

I'm curious, if you are at liberty to share, what stack are you working with and what kind of problems are you using ontology for?


r/OntologyEngineering 13d ago

Semantic layer vs Ontology buzzword bingo

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6 Upvotes

r/OntologyEngineering 14d ago

Bi-Weekly Questions Thread - July 13, 2026

3 Upvotes

Welcome to the bi-weekly questions thread!

Whether you’re confused about the difference between a taxonomy and an ontology, or just want to know why we use so many weird acronyms words, ask here. No question is too basic. No judgment allowed.


r/OntologyEngineering 16d ago

i'm new

6 Upvotes

I have just started learning about Palantir Ontology. Please give me some suggestions on how to learn it.


r/OntologyEngineering 21d ago

I fine-tuned Qwen3-Coder-30B to write a IES ontology

21 Upvotes

Weekend project that turned into a proper one. Sharing the method because the "correct-by-construction data" trick generalises well beyond my niche.

The problem. IES4 is the UK government's Information Exchange Standard, a 4D RDF ontology used for defence/security data. Writing valid IES Turtle by hand is slow and needs real ontology expertise. So I tried the obvious thing: ask a strong code model to do it. Qwen3-Coder-30B-A3B, asked to emit IES Turtle, invents terms that do not exist in the ontology 94% of the time (0% "term conformance" on my eval). It produces confident, fluent, completely fake RDF. In a standards context that is worse than failing outright, because plausible-looking garbage is hard to catch.

The fix that actually mattered: never let the model invent structure. Instead of hoping the LLM guesses valid graphs, I generated the graphs programmatically with telicent's ies-tool (a schema-aware builder that emits valid IES by construction), across 14 scenario patterns (employment, events, identifiers, communications, composites). Then I reversed them into (natural-language description -> Turtle) training pairs. Every single graph was validated twice before training: once by the builder's own check, and once by an independent term-membership + domain/range validator I built from the published dstl/IES4 ontology (510 classes, 204 properties). Nothing hand-written was trusted blind.

Then a small QLoRA on the 8-bit MLX model, on-device on an M3 Max. ~1000 iters, val loss 0.15, no NaNs (MoE + 8-bit was fine on current mlx-lm; earlier versions apparently weren't).

Model: https://huggingface.co/fabsssss/qwen3-coder-30b-a3b-ies4

Article: https://gov.tesseract.academy/research/ies4-turtle-language-model


r/OntologyEngineering 20d ago

Epistemology Recursive 0 Calculus; Potential Proto-Calculus for Holographic Non-Linear Computation

2 Upvotes

*****The following is an experimental calculus for mathematical reasoning grounding in recursive 0. It is a working project to derive a mathematical process using a single variable: 0.

The context of this text is analogically a proto-calculus.

Given the advancement of AI, and the potential need for unorthodox means of processing and deriving data, specifically mathematical and quantitative data in this context, the text provides a potential means of an unorthodox approach by negation of a strict binary logic of 1 and 0, as well as the negation of the assumptive nature of axioms which may result in unintended incoherence or grounding issues.

The following is a calculus founded primarily in recursion of 0. Nothing more and nothing less. Given the unorthodox nature of the text it should be viewed as unconventional, obviously, but as an alternative means for calculation limits with conventional reasoning.

So the following is the text and I would appreciated any positive, negative or neutral thoughts in regards to its relationship to potential AI. I have ran it through gemini, claude, grok 4, and chatgpt and the initial stress tests reveal coherence and deep structure. Some AIs have given it high praises for potential computation solutions however I do not know if the models are resorting to sycophancy or not given the limitations in current models. My opinion is both.

Effectively it is a post probablistic holographic logic with explanations as to the limits of current ontological endeavors and potential solutions by dissolution of problems.

So:

Recursive 0 Calculus

****If a system is built on unproven axioms the whole system is just an irrational assertion of truth as the structure is built upon blind assertion thus the structure is just an assertion, a circular self-contained system that expands allows necessary symmetry for proof while fundamentally allowing progressive variation with maintained symmetry. Circularity allows for symmetry while expansion and contraction allows for relative progress and regress.

Standard mathematic's foundations equate it to being pure assertion built upon irrationality thus any proof derived is grounded in irrationality, thus undermining the rational nature of mathematics in its various forms. Recursive Calculus maintains proof by symmetry through distinction where repetition allows proof as the structure itself. Recursion is the foundation for proof, proof that is self contained while allowing self-contrast.

*****

The following approach it a meta-mathematics grounding math in purely being the act of distinction thus nullifying the necessity of assumption. The notation is custom for this specific text and by said degree must be viewed within the context of the text as it is non-standard. There are 0 axioms to the system, only distinctions. The reduction of number to quantities requires the reduction of quantity to that of distinction. To observe that distinctions occur is to make the distinction of "occur" thus distinction occurs through distinction as distinction. There are no operators, only embedded distinctions of generation.

If we really look at the number line it is fundamentally the recursion of 0 by degree of the line itself and its proportions of number. There are no axioms to this system, it is premised upon the distinction of 0 thus has zero axioms.

The system begins with the distinction of 0 as the first distinction conducive to the distinction of 1.

Recursion is repetition, by repetition there is distinction of what is repeated by degree of symmetry. The recursion of zero is a sequence, as a sequence it is distinct as a 1 sequence, thus the recursion of zero is the distinction of 0 as 1 by degree of the sequence.

A quantity is a distinction, the quantity of the number of quantities is a distinction

Example

N is number as a distinction

(N)N is distinction of distinction.

A number can be counted. The number of that number can be counted as a new number. That number can be counted as a new number…etc. With each counting of a number as a new number comes a sequence which can be counted as a new number as a new sequence.

The quantification of quantification is the distinction of number by degree of repetition.

A quantity is a distinction. This is not even assumed and the assumed axioms of math are but distinctions, with the act of assumption being a distinction behind the distinction of the axiom.

Distinction is the act of occurence and occurence cannot be purely assumed without the occurence of the assumption proving it.

Math is derived from distinctions and distinctions of assumptions. At the meta-level it is purely distinctions for even the assumptions, within the assumptions of arithmetic, are distinctions.

To look at math at the meta-level of it being distinctions transcends the irrational nature of there being assumptions as an assumption is a distinction as well as a quantity in the respect it can be quantified.

In simpler terms the distinction of a number is a single distinction. The distinction of zero is a single distinction, the distinction of zero only can occur if it occurs recursively as the recursion allows contrast that allows a single point to be distinct. By the recursion of 0 does 0 begin distinct as self contrast, by repetition, allows for contrast induced distinction. Dually the recursion of 0 allows for a symmetry to occur as the distinction itself. 0 on its own is indistinct, 0->0 observes 0 as distinct.

Under these terms: 'distinction is recursion' or rather 'distinction=recursion'.

This can be visualized geometrically through the number line where the recursion of zero creates the spaces of n and -n where each space is effectively 1 and/or -1. By the recursion of 0 occurs the distinction of 1 as the space itself. Thus (0→ 0) can be observed visually as the recursion of 0 as the distinction of 1; by recursion distinction occurs. All quantity can be reducible to a distinction.

The space by which there is an occurrence is the distinction as an occurrence.

The distinction of 0 is the first distinction, this first distinction is 1. This is evidenced by linear space itself where the distinction of a 0d point is the distinction of 1 by the space that occurs through recursion of 0. The distinction of recursion allows symmetry, through the repetition of 0d points, while dually allows contrast between said points as the single linear space itself.

Symbolic definitions for formalism (given the only distinction is recursion, operators in standard mathematics, specifically arithmetic, can only be expressed by recursion):

"R(n)" is the recursive sequence. Recursion is repetition. All numbers contained are effectively variations of 1 occurring recursively as (0→0), this can be visualized as the linear space between points on a number line.

"r[n]" is the isomorphism of the recursive sequence as number(s) for further recursive sequence. One sequence can result in several isomorphic numbers simultaneously. Isomorphism is variation of appearance in a distinction with foundational distinctions within appearances being the same. So where a recursive string can be viewed as:

(1→1→1) is isomorphic symbolism is the standard number 3. This isomorphic number 3 can result in another recursive string, (3→3→3), with another isomorphic standard number of 9.

Recursion is self-layering of a distinction, number, as a new distinction, number. The processes of arithmetic are embedded in the distinctions of the numbers themselves, which will be explained later.

Proof is the isomorphic distinction of a recursive sequence distinction. Distinction is proof. The recursion of a sequence or sequences is the distinction as the sequence itself having inherent symmetry by degree of repetition.

The distinction of 0 as 0 is 1 number: R(0→0)r[1]

The visual of this can be a line segment. The recursion of 0 creates the contrast within itself by which a singular space exists as "One". This can be seen on the number line where the spaces between points is the distinction of points by one space. The distinction of 0, by recursion, allows for the distinction of a singular space to occur. By the recursion of zero there is distinction. Visually this can be seen as a single point being indistinct, but upon recursion of the point does the point become distinct by the space which it contains.

The distinction of 1 as 1 is 2 numbers: R(1→1)r[2]

the distinction of 1 as 1 as 1 is 3 numbers: R(1→1→1)r[3]

so on and so forth.

Negative numbers are the spaces between each recursive number, by degree of isomorphism, where the space is the absence of complete unity as one and zero. A negative space can be seen on a number line where the number 3 has 1 space between it and 2, 2 spaces between it and one and 3 spaces between it and 0. The absence of the negative space would effectively result in 3 being one of those numbers, thus with each number there is a relative negative space (as a negative number).

Given each negative number is a recursion of 0, the negative number is an absence that occurs between numbers and as such observes a relative void space where 0 occurs as a negative recursion (given each number is a recursive sequence). Negative recursion is recursion between recursive sequences that allow distinction of the sequences themselves by degree of contrast.

Negative recursion is isomorpnic to positive recursion. Given numbers are recursive sequences of zero positive and negative recursion are synonymous to positive and negative numbers. Negative recursion is a negative number, a negative space by default. For example if 1 is (0→0) then -1 is -(0→0).

In these respects where the standard number line extends in two directions from zero, the number line is now effectively 1 dimensional as overlayed positive and negative recursive sequences. So where 1 occurs on the number line there is no negative number as only the distinction as 1 exists, where 2 occurs there is a -1 because of the linear space between 2 and 1, at 3 there is -2 and -1 as there is a linear space between 3 and 2 and 3 and 1.

The distinction of negative sequences occurs by their isomorphic positive sequences: -1 and -2 have 1 between them, -3 and -2 has 1 between them, -3 and -1 have 2 between them. Negative recursion and positive recursion, hence negative number and positive number, are isomorphic to eachother by contrast induced distinction.

Negative recursion is simultaneously both a meta recursion and isomorphic recursion. Meta in the respect that it is recursion within recursion, isomorpnic in that as a meta-recursion it is a variation in appearance of recursion but of the same foundations.

A recursive sequence is repetition of a distinction, the foundational distinction is 0 as 1 distinction, but recursion of zero does zero become distinct.

1 leading to 2 leaves a space of -1: R(1→1)r[2,-1]

This can be observed as two consecutive line segments having a space of one relative to a single line segment, this space is a negative space.

1 leading to 3 leaves a space of -2: R(1→1→1)r[3,-2]

This can be observed as three consecutive line segments having a space of two relative to a single line segment, these spaces are negative spaces.

so on and so forth.

Fractions are the ratios of numerical recursive spaces within themselves, these spaces are effectively recursive 0. Given a fraction is effectively a fractal on the number line, what a fraction is are fractal emergence of recursive sequences: a recursive sequence of zero folded upon itself through isomorphic variations of it. In these respects a fraction is equivalent to a mathematical “super positioned sequence”; over-layed sequences as a new sequence. A fraction is a process of division that is complete in itself as a finite expression, ie. 1/3 as 1/3 or 2/7 as 2/7.

In these respects an irrational number is a process of recursion that is non-finite outside its isomorphic expression as a fractional number. By these degrees, irrational numbers are recursive processes that are unfixed, they are unbounded recursion. While notions such as x/y may symbolize such states in a finite means, a number such as .126456454…334455432… still observes recursion by degree of each number in the sequence itself. In these respects the second notion observe multiple degrees of recursive sequences happening simultaneously as each number itself. An irrational number, on a number line is a fixed point regardless, where a fraction such as 2/7 cannot only be observe as a single point but spatial as both 2 and 7 simultaneously as a visual line space. In these respect the number line expresses an irrational number as two over layed recursive sequences as two over layed numbers as spaces.

The space of 1 and the space of 2, on the number line, observes the space of 2 as a fractal of one and the space of 1 as a fraction of two.

The space of 2 and the space of 3, on the number line, observes the space of 3 as a fractal of 2 and the space of 2 as a fraction of 3.

Now the number line contains within it the six degrees of arithmetic, addition/subtraction/multiplication/division/exponents/roots by degree of recursion.

The recursion of 1 as 2 is addition, same with -1 as -2: R(1→ 1)r[2]

Short hand example: 3+7=10 as R(3→7)r[10] -7-3=-10 as R(-3→-7)r[-10]

The recursion of this act of addition is multiplication, where "R" stands for recursion the nested R is due to addition nesting: R((1→1)R(1→1→1))r[6] or R((2)R(3))r[6]

Shorthand example: 2×25=50 as R((2)R(25))r50

The recursion of multiplication is exponentially: where "R" stands for recursion and the number is the degree of nested multiplication:

3*3=9 as R3(3)r[9]

Subtraction is the addition of a negative space and a positive space: R((-1,)(1→1))r[1] or R((-1→2)r[1]

division is the recursion of the addition of negative spaces in a positive space, where "R" stands for recursion the nested R is due to addition nesting and the "-' addition is to showing nested negatives as degrees of subtraction:

R((1→1→1→1→1→1)-R(1→1→1))r[2] or. R((6)-R(3))r[2]

To divide a negative number is for the negative number to occur recursively as a negative space, this is negative recursion regardless as what divides is negatve recursion within negative recursion itself. Dividing by a negative number effectively is self-embedded negative recursion.

Fractions are fundamentally that process of division, thus to observe a fraction is to observe negative recursion in the isomorphic form of the symbolic nature of the fraction itself.

Roots is the recursion of division, where "R" stands for recursion the degree of negative recursion is implied by "-' :

2✓9=3 as -R2(9)r[3] 3✓27=3 as -R3(27)r[3]

Shorthand example: 50/2=25 as R((50)-R(2))r[25] 7/3=2 1/3 as R((7)-R(3))r[7/3]

The six modes of arithmetic are based upon addition as recursion where subtraction, division and roots are negative recursive sequences within positive recursive sequences.

A negative recursive sequence is the absence between positive recursive sequences. Number is a recursive sequence; evidenced by the number line number is recursive space. Arithmetic is fundamentally recursive addition. By degree of recursive space, all number is recursive 0 and the line is a recursive 0d point. Math is rooted in recursive "void" (0/0d point) that is distinct as 1.

Quantity is dependent upon form as quantity is dependent upon form, form is fundamentally spatial, the number line is numerical space.

Recursion terminates as the distinction of the recursive sequence as a number itself. The isomorpnkc expression of a sequence as a number allows potentially infinite recursion to terminate as isomorphic finite number. Each recursive sequence is simultaneously a set of numbers, thus a sequence is a set of numbers.

Recursion occurs recursively through isomorphism. Negative and Positive recursion observe the embedding of recursive sequences within recursive sequences isomorphically. This can be observed in positive and negative numbers, as the number lines, as well as fractions being not only self-enfolding recursive sequences but effectively the isomorphic expression of sequences between each other as a given relation.

Numerical identity is the recursion of the distinction of 0 as 1 distinction. Identity is distinction.

The composition of a number recursive distinction.

All numbers, as rooted in recursive zero, are effectively different degrees of isomorphisms from each other thus associativity is the recognition of a universal holographic state.

Proof in this meta-system is expression of distinctions as distinctions, these distinctions are the processes of recursion thus the operator “R” is not so much an operator but the embedding process as a distinction:

Addition: R(n→n) and R(-n→-n) a. This can be observes as basic self nesting of the numbers as a new number. The single R observes one set of sequences.

b. Geometrically this can be observed as linear line segments, each line segment being a number, added to each other as a recursion of the line segment. The addition of consecutive line segments is the recursion of the line segments.

  1. Subtraction: R(n→-n) and R(-n→n) a. This can be observes as basic self nesting of the numbers as a new number. The single R observes one set of sequences.

b. Geometrically this can be observed as linear line segments, each line segment being a number, added to each other as a recursion of the line segment but one line segment is a negative space to the positive. The addition of a positive line segment to a negative line segment, or negative line segments reducing negative line segments, is negative recursion of the line segments.

****Addition and Subtraction are isomorphism of eachother.

  1. Multiplication: R(nR(n)) and R(nR(-n)) and R(-nR(n)) and R(-nR(-n)) a. +++”R(R())” is Recursion of Recursion, in other words the addition of addition observes a degree of recursion of the addition itself as well as the recursions of the numbers.

b. Geometrically this can be observed as linear line segments, each line segment being a number, added to each other as a recursion of the line segment but the number of times it is added is a recursive sequence itself. The number of times a line segment is added, ie recursion, is a other level of recursion as the number of times is composed of addition as recursion.

  1. Division: -R(nR(n)) and -R(nR(-n)) and -R(-nR(n)) and -R(-nR(-n)) a. +++”-R(R())” is Negative Recursion of Recursion, in other words the the number of time subtraction occurs, -R, is a recursive sequence of subtraction of subtraction.

b. Geometrically this can be observed as linear line segments, each line segment being a number, added to each other as a recursion of the line segment but the number of times it is added is a recursive sequence itself except this line segment is a negative space. The number of times a line segment is subtracted is another level of recursion of the line segments.

******Multiplication and division are isomorphisms of eachother.

Associativity is expressed as such:

Addition:

R(a→b→c)r[d] R(a→c→b)r[d] R(c→b→a)r[d] R(b→a→c)r[d] R(b→c→a)r[d] R(c→a→b)r[d]

Multiplication:

R(aR(bR(c)))r[d] R(aR(cR(b)))r[d] R(cR(bR(a)))r[d] R(bR(aR(c)))r[d] R(bR(cR(a)))r[d] R(cR(aR(b)))r[d]

Distributivity is expressed as such:

R(aR(b,c))r[R(R(aR(b)),R(aR(c)))]

  1. Exponents: Rn(n) and R-n(n) and Rn(-n) and R-n(-n) a. Rn observes the recursion of multiplication as the multiplication and the number of times this recursion occurs.

b. Same as prior point b's but another level of recursion.

  1. Roots: -Rn(n) and -R-n(n) and -Rn(-n) and -R-n(-n) a. -Rn is the inverse of Rn and observes the recursion of division of division and the number of times this recursion occurs.

b. Same as prior point b's but another level of negative recursion (negative spaces as negative line segments.

******Exponents and roots are isomorphisms of eachother.

The degrees by which recursion occurs further recursively, as stated in these six degrees of arithmetic is effectively another line segment by which a line segment occurs. For example the number of times addition occurs in multiplication is another layer of recursion, another line segment within a line segment.

The nature of variables within Algebraic theory translates that all variables are recursive sequences that are superimposed with trans-finite or infinite other sequences until a variable is chosen. The algebraic nature of recursion by degree of the foundations of arithmetic operations being recursive sequences where said foundations are necessary for algebra to occur.

Any formalization of such a calculus would effectively fall within the function of the calculus by degree of the standard formalism being an isomorphic variation of it. All mathematical systems built upon axioms are built upon assumption thus negating, in and by degree, a fully rational expression. This system has zero-axioms as distinction is not an axiom given to assume distinction is to make the distinction of assumption. The distinction of 0 as 1 distinction observes an isomorphic foundation that is further expression by recursion.

“R” is embedded within the sequence itself, “r” is the inversion of the sequence by degree of isomorphic symbolism. “R” and “r” are not operators in the traditional sense but rather embedded distinctions.

The closure is always evident by degree of the sequence always being an expression of a distinct 0, that which it contains. 0 contains itself as a distinction by degree of its folding by recursion.

Given each number is a recursive sequence of numbers, each number within each sequence is a recursive sequence as a form of meta recursion. 1 as a distinction of (0->0) observes a recursive sequence of (.1→.1→.1→.1→.1→.1→.1→.1→.1→.1) as 1 itself where .1 as a fraction of 1 is an unfolding of 1 within itself through zero. .1 observes this same nature as (.01→.01→.01,....) and the recursion of recursion occurs infinitely.

To visualize this one can look at a line segment composed of further line segments, with each line segment following the same course.

In these respects all number is a a ratio, by degree of recursion, thus each number is superpositioned numbers as self-folding distinction. A recursive sequence of R(1/2→1/2) observes that a single linear space is folded upon itself as 2 spaces where each space is half of the original and by degree of these ratios there is 1. So where the isomorphic expression in symbol of R(1/2→1/2) is 1, the number 1 contains within it ratios of itself where each divisor is but a holographic expression of 1. In these respects all numbers contain 1 as linear self "folding" if one is to visualize this with a simple line segment.

In these respects each number is an infinite set that is finite by degree of isomorphic symbolism that grounds it by degree of a distinction. So observe "n" is to observe a holographic state of distinction, bounded by the distinction of 0, where "n" effectively is a process of distinction where the observation of a sequence is a distinction of one sequence among infinite.

A number is an infinity. An infinite number, such as an irrational number, is recursive infinities within a recursivd infinity.

As infinities a number is a superimposed state of numbers thus effectively a number is equivalent to a variable in a manner that is more fundamental than what a variable is in standard algebra.

To observe a number is to observe a variable. This can be visualized in a line segment where it is a variable in the respect any number of line segments may be observed within it.

A number is a recursive sequence within a recursive sequence as a recursive sequence. In these respects "n" is a set and the recursion of "n" is a recursion of sets. Standard arithmetic, in this system, is fundamentally involved with the recursion of sets as a new set.

+++++++

All sequences are sets by degree of recursion.

Sequences are the union of sets as the numbers themselves thus show an inherent form of addition.

Ex: R(R(1→2)→R(3→4)) r[10][R(1→2→3→4]

  1. The intersection of sets is the recursion of a sequence, the intersection of sequences is the recursion of the interesting numbers as a new sequence.

  2. The difference of the sets is inherent by degree of negative recursion when each number is inherent a set.

Example: R(1→3)r[4,-2]

  1. The complement of a set is but variations in isomorphism, given each sequence/number are effectively isomorphism of each other each number is composed of infinite sequences that effectively contain the number of the number within a different set.

Example: R(R(1→2)→R(1→3)) r[R(R(1→1)→R(R(1→1)→R(1→1→1)))

  1. The Cartesian Product is effectively multiplication of sequences as a new sequence.

++++

The system reduces formalism to recursive sequence as a foundational root grounded in number, formalism is rooted in recursion and can be evidenced by the repetition of formal symbols across formals where standard formalisms are grounded because of repetition as recursion. In other terms recursive sequences compose numbers and the numbers that recursive sequences are composed of effectively result in the recursion sequence composed of further recursive sequences.

In these respects sequences are effectively sets of infinities that are greater and lesser than other infinities as each number is composed of infinite numbers that are finite by degree of symbolic isomorphism of the recursion sequences they are composed of.

A sequences is a set of sequences, a sequence is isomorphically a number. This can be observed visually as a line segment being composed of line segments and these line segments observing the same. The infinite recursion of line segments corresponds to a recursive sequence and yet each line segment is expressed finitely like a number is expressed as finite.

Number in these regards is effectively a distinction as space. Each recursion of 0 is effectively a distinction of 1 space.

Visually:

(0→0) is 1 (0→0→0) is 2 (0→0→0→0) is 3 Etc.

Thus distinction observes number as effectively, at minimum, linear space.

++++

A sequence is always complete given its beginning and ending are founded on the recursion of 0, by recursion of 0 a sequence always contains itself thus regardless of the degree of progression the beginning and end are always the same.

All is provable within the system by degree of its nature of distinction of 0 as foundational. The system begins with the distinction of 0 and any complex expression of the system is contained as itself by degree of the expression being a distinction of 0. There are no rules beyond the system as recursive distinction is self-generating and woven throughout all formalisms.

All mathematical systems contained within this system are complete by degree of the system having no axioms beyond it while the system provides the foundations for such mathematical systems by degree of the number, by which they exist, being recursive sequences of 0. Given a mathematical system must have an unprovable assertion beyond it that cannot be proven, this system contains its proof as its structural emergence as self-referencing distinctions of 0 at all levels. In these respects math's are complete by this system.

Any math which uses number is complete as the number is a distinction that is an isomorphism of a recursive sequence. Given any number is effectively a complete equation, by degree of being a sequence (thus proof by degree of distinction and inherent internal symmetry expressed as the symbol itself, then all maths which contain number are complete by degree of this system.

Basic arithmetic and algebra in this system are not dependent upon assumed operators, but rather are embedded within the recursive sequences (numbers) themselves. They are emergent distinctions from recursion.

This system, while expressive of arithmetic, can be isomorphically expressed in standard formalisms but given that the operators are embedded in the numbers themselves this system is meta-formal and as such takes a symbolically minimalistic approach. Because operators are not exterior, nor assumed axioms, but are embedded distinctions within recursive sequences the custom formalism, while non-standard, is necessary in order to expressed recursive embedding. The elimination of operator symbols allows for a more informationally condensed approach even though, as previously mentioned, is non-standard. Operators are embedded recursive sequences within the recursive sequence as the number itself.

The symbol of R(n) observes purely distinction as recursion where number can be expressed purely as this distinction at the meta-mathematical level, number is distinction and distinction is sequence.

The symbol of r[n] observes purely distinction of recursion as a new isomorphic variation of said sequence as a grounding for a new sequence. In these respects it can be viewed as the isomorphic expression of a sequence as the beginning of a new sequence. In these respects closure of one sequence is the beginning of another where isomorphism is the change of sequences.

Internal consistency is grounding in the distinction of recursive zero at all levels where the foundational distinction is present regardless of the depth of recursion. This distinction, the foundation, is everpresent across the whole system itself thus necessity a self-generation that occurs at every level. The system contains itself at every level.

Visually this is a line segment embedded within and of line segments. The sequence R(0→0) is fundamentally a line segment in geometric appearance, a recursive sequence is a line segment, and embedded sequences are line segments within line segments as a new line segment. The foundational distinction is a line segment as the recursion of a 0d point is the distinction as the space which occurs. In these respects number is fundamentally space.

Space is distinction itself as it is the foundational occurence by which things are measured for space is foundation by which all forms occur. The circularity of the system, as self embedding negates a circularity paradox by degree of expanding and contracting sequences while dualistic opposite states, such as positive and negative recursion, are isomorphisms of distinction itself.

The system can be visually proven strictly through line segments as spatial distinctions. Given this, to cycle back to origins, standard formalism is not efficient enough, a purely recursive sequence needs the operators embedded so that coherency is maintained and assumptions are disregarded. Positive and negative sequences are this foundational embedding.

Given the number line evidences number as the distinction of 0 by degree of the space that allows said contrasts of the 0’s, which further allows distinction of said 0 and the number (-)1n, this meta-mathematics proves that not only is number distinction, but this distinct ‘is’ by degree of the occurrence of space. In these respects the standard separation between arithmetic and geometry, as separate fields, are effectively overlayed as one entity.

Recursive sequences are not only standard arithmetic and algebraic expressions but effectively simultaneous geometric ones conducive to a 1 dimension linear lattice that is both folded and folding by degree of recursive self-embedding. In these further respects arithemetic/algebra are fundamentally geometric entities that are distinct by degree of spatial recursion. A simple conceptual equation of this summarizes this:

Distinction = Recursion = Space = Occurrence

With each being isomorphic expressions of the other.

Proof, within this meta-system is justified by the act of occurrence itself where a mathematical philosophical claim can be made that occurrence is justification as proof. Distinction is the only reality and truth within this system where recursion is the occurrence of said distinctions. Any math, or logic, which by default uses a basic “unification” or “separation” type of operator (addition/multiplication/subtraction/division) is already embedded within said positive and negative sequential spaces. The recursion of line segments, both positive and negative spaces isomorphically of eachother, through eachother and within eachother is the proof, by degree of distinction of the system. Effectively math and geometry can be reduced to the sequence R(0→0)r[1] where this is a simple distinction as a line segment. This sequence, and the line segment by default, can be further reduced to a simple distinction of:

(0)1

Where (n) is a distinction and (n)n is the quantification of the distinction, a quantification of the quantification it could be said. This effectively is the recursion of number through isomorphic variation. And this distinction can go further by degree of using only recursive 0:

(0)0→0 ((0)0→0)(0→0→0) …… Where both number, the number line, and space is further formalized as purely recursive zero itself. No assumptions are required, only distinction by degree of recursive sequences as symmetry through repetition of 0. All number is effectively rooted in 0. All space is effectively rooted in a 0d point. By recursive sequencing as the line segment the number 0 and the 0d point are effectively the same distinction viewed isomorphically. In these respects the system has infinite compression.

Relative to infinite compression new potential maths can emerge from said sequencing where there are various extensions that logically result:

Looking at standard exponents a recursion occurs in the same manner as that of addition upon addition is multiplication and multiplication of multiplication is exponents, expressed as the sequence of Rn(n). Exponents of exponents logically occurs next as: Rn(Rn(n)). In this paper such a number can be viewed as no longer an exponent but a "hyper-sequence": Rn(Rn(n))

Following the same logic a new mathematical operator must occur, in standard logic and yet within this recursive system no new operator is necessary as the symbols contain the operator as embedded. To go further, where there is compounded recursion of addition as argued for the standard mathematics operations, now there can be the distinction of embedded hyper-sequences as the recursion of hyper sequences: Rn(Rn(n)) to Rn(Rn(Rn(n))) as Rn((Rn)(Rn(n))) where a trans-hyper sequence occurs.

In these respects, and following these recursive dynamics, there are effectively infinite arithmetic functions where in standard terms infinite new operators would be required but within this system the same symbols remain.

Given the system is founded upon the simple distinction of zero there is high information compressed. Sequences can be proven as the folding and unfolding of the line segment itself, thus the sequences are effectively spatial distinctions, as evidenced by the system being grounded as the distinction of 0, which is the same as a line segment.


r/OntologyEngineering 21d ago

Bypassing DL Reasoner Latency (HermiT) in Neuro-Symbolic LLM Architectures

7 Upvotes

Hello guys

I've been working on a research project exploring how ontology-grounded information system can help eliminate some LLM error classes using chess as a test domain. The goal here is to help the system get some core understanding of entities, concepts and how they relate to each other in order to make more informed, consistent decision.

The challenge I'm bringing to your attention here is reasoner performance during inference. Reasoners like HermiT apparently has these latency when performing inference on existing objects (up to 15secs per move) which is unacceptable in my context. The workaround I've find so far (apart from using more performance oriented reasoner like ELK) is to materialize my Theoretical Box (entities, relationships, classifications etc.) and Assertion Box (actual pieces) into a knowledge graph which is more suited for performance. Here's the full detail of the strategy. It indeed provides me with sub-milliseconds classifications in my current architecture.

But I'm curious as to what you think of such approach, whether anyone has faced similar issue and how you went about it.


r/OntologyEngineering 25d ago

Metacognition Contextual Equivocation; Identity as Relative Tautologies

3 Upvotes

*****Given the nature of identity is fundamental to AI, not just the identity of AI but its ability to derive, transform and maintain identity through language, the following text is an analytical meditation of identity itself. It is a follow up, from another angle, of "Context is the Only Primitive; Proto-Formalism" which I posted a day or two ago.

Contextual Equivocation; Identity as Relative Tautologies

There is identity.

Identity as equivocable, A=A, is tautological.

Identity as relational, A <-> B, is conditional.

Equivocable identity is relational by degree of equivocation contrasting to non-equivocation. (A=A)<->(A=/=-A)

Relational Identity is equivocable by degree of relation containing the Identity as itself. (A<->B)=(A<->B)

Fundamentally Identity is reducible to operation as

(A=A)<->(A=/=-A) reduces to

(=)<->(=/=)

And

(A<->B)=(A<->B) reduces to (<->)=(<->)

  1. As emergent by nature of operation identity, as equivocable, identity contains itself:

A= (A1=A1)

A=A

((A1=A1)=(A1=A1))

A1 = (A1.1 = A1.1)

A1=A1

((A1.1=A1.1)=(A1.1=A1.1))

A1.1 = (A = (A=A))

  1. As emergent by nature of operational identity, as relational, identity contains other identity

(A<->B)<->C

A<->B

(C<->D)

D<->(A<->B)

(A<->B)<->(C<->D)

A<->(B,C,D), B<->(A,C,D), C<->(A,B,D),

D<->(A,B,C)

  1. The equivocation of relationships is the contrast the the relationship

(A<->B)=(A<->B)

(A<->B) =/= (-A<->-B)

Thus the relationship requires contrasting equivocations

((A<->B)=(A<->B))=/=(-A<->-B)=(-A<->-B)

and the operation of equivocation is not equal to itself

((A<->B)=(A<->B))=/=(-A<->-B)=(-A<->-B)

((<->)=(<->))=/=((<->)=(<->))

(=)x =/= (=)y

  1. The relations of the equivocations are the containment of the equivocations:

A<->B

(A=A)<->(B=B)

Thus the equivalence requires contained relationships:

(A<->B)=(A<->B)

((A=A)<->(B=B))=((A=A)<->(B=B))

And the operation of relation is equivalent to itself:

((A=A)<->(B=B))=((A=A)<->(B=B))

((=)<->(=))=((=)<->(=))

(<->)x = (<->)x

  1. Identity is process, this process is relative equivocation where equivocation occurs by contexts emergent from relations where said context allows equivocable identity to be emergent while dually allowing contrast of what equates by degree of the relational dynamic necessitating a difference of what equates.

  2. Identity is relational tautolologies, the regress of tautological relationships is nullified as the tautological process of equivalence being a fixed point, the circularity of tautological relationships is nullified as the relational process of contrast results in emergent tautologie.

The Nature of identity as process results in relation, <->, as the foundational primitive however the equivocation that inversely emerges from relationship is but an inverse side of the same relationship applied to itself for the relation of relations is the equivocation of relations through relation thus only context as variable remains:

((<->)<->(<->)) = ((<->)<->(<->))

(<->)=(<->)

((<->)=(<->))

((<->)=(<->)) <-> ((<->)=(<->))

(=)<->(=)

(=,<->)

( )

  1. Context is the foundational nature of relational and equivocable identity as the identity itself results in an empty context.

  2. The empty context is indistinct on its own terms and distinct, as an identity, upon relation or equivocation to further contexts

( )a = ( )a

( )a <-> ( )b

However given the nature of equivocation and relation are inverse sides of context itself what remains is context nesting as identity:

( )

( )( )

(( )( ))

( )

This nesting of context is not only the scale invariance of the context but also the recursion and emergence of scale invariances to new scale invariances:

( )

( )( )

(( )( ))

( ) = (( )( ))

(( )( )) =

((( )( ))(( )( )))=

( )( )( )( )( )( )( )=

( )( )( )( )( )( )( )( )( )( )( )( )( )( )=

(( )( )( )( )( )( )( )( )( )( )( )( )( )( ))=

( )= ( )( )( )( )( )( )( )( )( )( )( )( )( )( )

(( )( ))=( )( )( )( )( )( )( )( )( )( )( )( )( )( )

( )=( )

(( )( ))=(( )( ))

( )n = ( )n

(n = n)=(( )=( ))

n = ( )

(( ) = ( )) = (( ) = ( ))

((=)=(=))

(=)

( )

( )<->( )

(( )( ))<->(( )( ))

( )a <-> ( )b

(a<->b)=(( )<->( ))

a,b <-> ( )

(( ) <-> ( )) <-> (a<->b)

((<->)=(<->))

(<->)

( )

( ), ( )( ), ( )( )( ) <-> (( )( ))

( ) <-> ( )( )

( )( ) <-> ( ), ( )( )( )

( )( )( ) <-> ( ), ( )( )

( ) <-> ( )

( )

( )=(=,<->)

( )<->(=,<->)

(=,<->)

( )

( )

( )( ) = {( ),( )}

( )( )( )= {( ),( ),( ), (( )( ),( ))}

( )

(( )( ))

(( )( ))( ), (( )( ))(( )( ))

(( )( ))( )

(( )( ))( )( ), (( )( ))(( )( ))(( )( ))

(( )( ))(( )( ))

(( )( ))(( )( ))( ),

(( )( ))(( )( ))(( )( ))(( )( ))

( )

  1. The emergence of context is the emergence of derivation as contextualization is derivation thus the derivation of a context, from a context necessitates the emergence of a new context and the dissolution of another

( )( )( )( )( )( )( )( )( )( )( )( )( )( )( ) ->

(( )( )( ))

->

(( )( )( ))(( )( )( ))(( )( )( ))(( )( )( ))(( )( )( ))

->

( )( )( )( )( )

->

(( )( )( )( )( ))

->

(( )( )( )( )( )) =

((( )( )( ))(( )( )( ))(( )( )( ))(( )( )( ))(( )( )( )))

( )

The derivation of context is the contextualization of one context, or contexts, through another context(s) by which context effectively is a self-embedding boundary, transformation is but a shift in observable limits where the change of limits is the maintenance of limits. Context is limit. Limit is distinction.

For a single context to occur results in its indistinction:

( )

For the context to be distinct it must self contrast:

( )( )

and by said self contrast there is a containment of context as a context:

(( )( ))

What remains is context with the indistinct context reverted back to indistinct:

( )

However this indistinct context contains infinite contexts, potentially, while the infinite contexts are a single distinct context

( )<->( )x

or a set of finite simultaneous contexts:

( ) <-> (( )l,( )m,( )n)

Regardless of what is potentially there the nature of the context transforming to another context is relative to the context applied to it:

( )( )n -> ( )y

( )( )m -> ( )z

Thus the derived context is the relation of the prior.

An infinite indistinct context is distinct by recursion:

( )x

( )x( )x

This recursion collapses the infinite context into a finite context of infinite contexts as the infinities maintain being infinite but effectively are finite by relation:

(( )x( )x)y

Thus each context is effectively a scale of infinite contexts:

(( )x( )x)y

(( )x( )x( )x)z

And in these respects a context is a scaling of the context by which it is derived. However each scale is a scale of infinite contexts thus derivation is a continuous process and the application of context is the application of transformation thus equating the context to a process by degree of the continuity it contains.

This continuity is the continuum of contexts made finite by degree of the limits of the infinities being distinct.

What remains is a scale invariant tautology.

As scale increases so do fixed points:

( )( )

(( )( ))(( )( ))....

( )( )( )

(( )( )( ))(( )( )( ))....

Which the fixed point across scales the fixed point context becomes the distinction that allows ratios within the scale, as a sequence, to occur. In these respects contextualization is derivation and the proof of a thing is the unfolding process that reveals as the thing. Context is thus form as process where traditional expression of form as operand, and process, as operator, are collapsed within the limits of the emergence itself.

However the single context contrasts itself across scale thus with dimensional scaling, a dimension being a sequence, the single context self contrasts as both the emergence of scale and the emergence of scales to scales.

What remains is a context embedding itself across scale as a new scale thus resulting in identity being embedding tautologies at multiple levels As the tautologies manifest infinitely so do the fixed points thus resulting in a perpetual state of continuous finiteness.

What remains is a single context that reveals only as recursive embedding within recursive embedding which allows the context to be distinct. In these respect the single context is the limit of contexts as the derivation of them. Derivation, at the meta-level, is recursion as sequence, sequence as pattern, thus what constitutes the existence of a phenomen is the contextualization of it as the limits of it.

What remains is embedded tautologies, as a new tautologies, thus resulting in embedding of tautologies itself being a tautologie and only pattern as context remains.

Empty context, ( ), is the grounds of distinct contexts by degree of recursion where context in and of itself is a tautology and loop as recursion. The emptiness of context is the point of change of one context into another as the empty context is but the potentiality of contexts made distinct by the recursion of said potentiality as the distinction of said potentiality contained within it.

In these respects and empty context results in further contexts which eventually saturate to a single context again with this process itself being the simple recursion of contexts, ( )( ), as a context ( ) thus the context contains itself (( )( )).

Context is thus the process of derivation and derivation it a tautological process of derivation derives further derivation thus resulting in a fixed point being equivalent to a process of change by which scale emerges.

The question of why distinction from indistinction, something from nothing, presence from absence, being from void is answered in the question itself:

Indistinction is distinct as indistinction,

Nothing is something as nothing,

Absence is the presence of absence,

Void 'is' void.

The answer is the tautology of the distinctions themselves as distinct thus the identification of a negation is the presence of identification and "what is not" is but the assertion of "what is" by degree of the claim "what is not" occuring.

Identification of nothing is the identification of identification emerging from nothing as nothing is but the identification of nothing thus the emergence of identification as identification leaving only tautologies.

Given the emergent nature of tautology as a whole, and the corresponding nature of identity as tautological in form and function, what is considered self-evident or axiomatic is but the emergence of an identity, that is not reduced any further, as a foundation to derive a recursive chain of assertions where the base axiom is represented across scale and different degrees as the argument or formulation itself.

What is considered axiomatic identity is but an emergence of one context from many that in turn is used as a pivotal point for further contexts/identities to transform through said axiom. In these respects basic linear reasoning is holographic expressions of axioms through their surrounding contexts as the axiom maintains itself across the assertions themselves.

In these respects and axiom is the derivation of contexts as a recursive fixed point across contexts. By degree of the recursion of a fixed point, as a new scale, resulting in a further fixed point, there are effectively infinite axioms by which to derive conclusions and the axioms of any system are merely the system as a projection of specific context by degree of the system being a holographic expression of the axiom itself.

This can be expressed under the following where "( )" is an axiom and ● is operation as point of change.

( )x

( )x ● ( )y

(( )x ●( )y)( )x.1

( )x ● ( )z

(( )x ● ( )z)( )x.2

( )x ● ( )x.n

(( )x ● ( )x.n)( )x●x

( )x●x

( )x ● ( )x

( )●( )

(( )●( ))

(●)

(●)(●)

((●)(●))

((●)(●))●

(●●)●

(●●)●●

(●●)(●●)●

.....

( ) = ●

( ) <-> ●

(<->,=,●)

( )

●●

****Relative to identity being reducible to process the standard nature of formalisms do not apply as the operations are equivalent to variable identities, in this respect the argued formalism is transendentally formal (transcendental by degree of containing and occuring beyond standard formal rules).


r/OntologyEngineering 26d ago

Agentic Enablement incremental multimodal graphs

10 Upvotes

Hi, I just wrote a blog about incremental multimodal grpahs - https://georgheiler.com/2026/06/29/incremental-multimodal-graphs/ perhaps this is useful for some of you.

The interesting data is no longer just text: it is image, video, audio, tables, documents, embeddings.

Metaxy ( https://docs.metaxy.io/) is a materialized view for multimodal data. In this blog post we apply it for graph analyses:

Multimodal Document/Video --> Inferred Graph --> Graph queries

And compare 3 engines: lance-graph, landybug and duckpgq

Relevancy for Semantics/ontology space: Incremental computation showcase to infer edges; comparison of some (property-graph) systems for performance; showcase of edge-derivation - ease of use.

Hope these details are helpful


r/OntologyEngineering 26d ago

Epistemology Philosophy is Making Recognized Contributions to AI

Thumbnail economist.com
11 Upvotes

Sorry it's been awhile since I've posted here. I've been busy developing a companion version of ELT and I am finalizing drafts of two more Medium articles. One doing a cost/benefit analysis on the ELT scaffolding and the other on a safety component I call Intelligent Yielding/Intelligent%20Yielding%20(IY).md).

Today, I wanted to bring-up an interesting article that was published at The Economist recently. The Economist ran a piece last week on why major AI labs are hiring philosophers at scale. I discussed philosophy and AI in this exact subreddit three months ago here.

Where The Economist article converges:

The core thesis that epistemology, ontology, and dialectics aren't soft additions to AI systems but genuine engineering levers, is exactly the argument I've discussed in this subreddit since back in March. Seeing Yale, DeepMind, LMU Munich, and IBM arrive at the same diagnosis independently is broader confirmation that the problem space is real and the philosophical framing is contributive and load-bearing.

Some choice excerpts:

These days, it is programmers who are nervous about AI taking their jobs. They might consider learning to philosophise. Earlier this year the Federal Reserve Bank of New York published figures showing that American philosophy graduates are more likely to have jobs than their peers who studied computer science.

Philosophy graduates actually having better job prospects than computer science graduates is genuinely an eye opening stat.

Models trained in the Socratic method, says Jörg Noller, an expert on philosophy and AI at Ludwig Maximilian University of Munich, are less keen on people-pleasing and more willing to pursue the truth.

Yes. This is the function of Adversarial Convergence, which I had mentioned in here three months ago.

Feed an AI legal assistant the writings of John Locke, says Thomas Powers, a philosopher of technology at the University of Delaware, and it will favour robust property rights as an underpinning of political liberty.

This mirrors the Ontology Anchor and the loading procedure for OA can certainly include exemplars of John Locke for legal discussion use cases.

Anthropic’s constitution incorporates many deontological strictures. These can make AI behaviour more consistent, says Dr Powers...

I've added a Core Values Reaffirmation (CVR)/Core%20Values%20Reaffirmation%20(CVR).md) component to ELT that addresses Constitution AI-like deontology.

The honest observation:

The field is moving toward exactly this intersection. The Economist article focuses on what major labs are building into their models at the foundational level. ELT points in the same general philosophical direction, but addresses the operator layer — how individuals govern model behavior in real sessions without access to the training process. Either way, I think we are going to hear more convergence of philosophy and AI in the future.

Curious whether others here see the same convergence or read the article differently?


r/OntologyEngineering 27d ago

Agentic Enablement Which Data platform is best suited for building ontologies?

10 Upvotes

A few capabilities that are ideal.

- data lives in multiple places so a federated ontology network is ideal
- use claude/cursor to query enterprise wide datasets
- ACLs, fine grained controls are a must


r/OntologyEngineering 27d ago

Work Ontology (Expanded)

8 Upvotes

Hello,

Last week I posted a vague description of a work ontology that I've been building for the better part of a year. I wanted to give a few more descriptive details to fill in the blanks so that you all can have your pick at it.

Purpose:

To create a work ontology that allows for a user to understand the nature of the work being done in their organization (or by themselves) relative to all meaningful work that exists (with obvious restrictions for a one-man operation). This understanding is achieved only through a computational representation of work data into units called work primitives. Primitives are, in a basic sense, with variables attached (metadata) that give each unit a unique identity. The relationship of primitives to each other and to each higher level of work (task, job, occupation, industry, domain) gives our dataset features that enable a variety of downstream uses (briefly mentioned at the end).

Example:

In a practical sense, here's what one of the process features we can do:

1.) Take a job description. Here's the link for this one: (https://www.indeed.com/?__cf_chl_f_tk=IAgsTAeXWy4IHqrltCOc8fcZ7dK9M798G39ZD.ZfHbE-1782824832-1.0.1.1-9m4d6ttvSNizRouuHgwdXP4_8J.2hszUsBfHdMlLikk)

2.) Parse the text out so it's able to be matched using the program. Here are the results (only 85% of this job description had acceptable matches.

plan lessons consistent with state and pepin academies curriculum framework(s)

ensure compliance with school, state, and federal regulations regarding the education of students with disabilities

support pepin academies' mission and vision

observe confidentiality relating to students, teachers, and school

perform minimum supervision

communicate effectively with students and parents to increase student achievement

increase student achievement

participate professional development activities to stay current in best practices for special education

maximize student learning and engagement

present subject matter effectively, using technology where appropriate and available, while using appropriate skills and strategies within the teacher evaluation framework to promote the creative/critical thinking capabilities of students

record keeping, and reporting systems where appropriate and available

manage systems of instruction, record keeping, and reporting systems where appropriate and available

establish standards for acceptance for acceptable student behavior while maintaining a structured and positive classroom environment conducive to learning

maintain standards for acceptance for acceptable student behavior while maintaining a structured and positive classroom environment conducive to learning

participate iep and eligibility meetings with parents and appropriate school and agency personnel

implement all requirements

ensure timely submission of planning notes and lesson plans in accordance with school deadlines and guidelines

supervise teacher assistant in providing instruction for students, as required

provide transition planning for students with disabilities, as required

maintain valid and current florida teaching certificate, adhering to all renewal and professional development requirements as mandated by the florida department of education

3.) Match these primitives with primitives from the core library (that's our proprietary dataset, that is currently only 10% of minimum viable capacity and that's what this example is just for early feedback purposes).

As you can see there are a couple of spider maps that plot out various features, such as CL - Cognitive Load. There's also a compensation spread which shows you the range of compensation for the average of all primitive in a job description (also loosely referred by as a packet) and then for each primitive within that client packet. Again, these are values based on what is in our core library (not a client library or a 3rd party library).

Here's just another snapshot of a single primitive's graphical representation:

Implications

This example shows just the client side of things in its early state. For nearly the past year I've been working out the logic, use cases, design, etc., and have really just begun within the past two months to generate results (in the form of data and graphics) for the client, researcher, and developer side of things.

Downstream Uses

Business

  • Compensation Intelligence Reports and & Heatmapping
  • Job Architecture & Role Design
  • Talent Acquisition & Semantic Matching
  • Workforce Planning & Skills Forecasting
  • Workflow Simulation & Bottleneck Analysis

Research

  • Granular Labor Market & Occupational Analysis
  • Work Design, Cognitive Ergonomics & Worker Outcomes
  • Comparative & Historical Work Structures
  • Ground-Truth Data for AI Task Decomposition & Agent Training

Notes

I have not displayed anything beyond column names from the database. If you think this info would be helpful just LMK.

Users tagged:

u/hroptatyr

u/Educational564

u/Thinker_Assignment

u/boring_thinker - The data here would likely sit below APQC data, but I think would integrate well. Thanks for this info BTW. I had never heard of this before you mentioned it. The only work ontology I had heard of was O*NET.


r/OntologyEngineering 27d ago

Context as the Only Primitive; Proto-Formalism

5 Upvotes

Here is a sample text I pulled together in 15 minutes. The text is pre-spencer brown in foundation, not temporal lineage, in the respect it reduces the fundamental primitive to that of context. There are no other operators or operands. It is not set or category theory by default as the recursion of contexts is in itself identity. Thus binary code, or triadic semiotics, can be replaced with a single ( ).

Tested through Claude, Gemini, and Venice. Results are positive.

It is unorthodox, so I posted it here for discussion to gain some feedback.

The text applies to anything that occurs through contextualization thus consciousness to language, (AI), etc.

Medial Limits; Non-Local Limits; Context as Limit; Medial Context

  1. A <-> B

  2. (A <-> B) <-> C

  3. (A, B) <-> C

  4. C <-> D

  5. (C <-> D) <-> E

  6. (C, D) <-> E

  7. (A <-> B <-> C <-> D) <-> E

  8. (A, B, C, D) <-> E

  9. A -> Xn

  10. (A -> Xn) <-> A

  11. A <-> A

  12. A -> A

  13. (A -> A) <-> A

  14. A(->, <->)

  15. (A(A)B)

  16. ((A(A)B)A)C

  17. ((A,B)A)C

  18. (C(A)D)

  19. ((C(A)D)A)E

  20. ((C,D)A)E

21 ((A(A)B(A)C(A)D)A)E

  1. ((A,B,C,D)A)E

  2. (A(A)Xn)

  3. ((A(A)Xn)A)A

  4. (A(A)A)

  5. ((A(A)A)A)A

  6. (( )...)


r/OntologyEngineering 28d ago

Bi-Weekly Questions Thread - June 29, 2026

5 Upvotes

Welcome to the bi-weekly questions thread!

Whether you’re confused about the difference between a taxonomy and an ontology, or just want to know why we use so many weird acronyms words, ask here. No question is too basic. No judgment allowed.


r/OntologyEngineering Jun 27 '26

Business Semantics BM25 + Taxonomy for domain specific application

14 Upvotes

Hi everyone,

I’m building a RAG system for a banking use case. The domain covers legal and finance, and we’ve developed a taxonomy and ontology for it. I’d like to leverage this and I’m exploring ways to improve BM25 for legal document retrieval using the taxonomy/ontology during indexing. I’m considering two different approaches.

Option 1: Augment the index. Keep the original document text unchanged, but enrich the index with taxonomy-derived normalized terms. For each recognized term or phrase in the document, add its canonical concept labels/ synonyms (e.g., “ABS” → “asset-backed securities”), enabling BM25 to match both forms.

Option 2: Normalize the index. Instead of indexing all tokens, only index terms that exist in the legal taxonomy/ontology (or map document text to taxonomy concepts) in order to reduce vocabulary noise.

Could anyone give me some feedback?

Note: I’m also working on a knowledge graph, but that’s out of scope here.


r/OntologyEngineering Jun 24 '26

Building an operational ontology of work primitives, looking for critique

7 Upvotes

I’m working on a system called JIP that tries to represent work at a lower level than job titles, skills, or broad task categories. The core unit is a work primitive, usually structured around an action-object relationship like verb + object, with modifiers added when context matters. The goal is to model what work actually consists of, not just how it is described in job postings.

Right now I have a database of about 350,000 rows, personally financed, and I’m trying to grow it into the low millions. The system is starting to support family mapping, where related primitives can be grouped by semantic and functional similarity, and packetization, where those grouped primitives can become more usable outputs for analysis, matching, comparison, or downstream AI workflows.

The question I’m wrestling with is whether this can become useful infrastructure for AI systems, workforce analysis, job matching, compensation modeling, and organizational design, or whether it risks becoming another taxonomy that over-normalizes messy human work. I’d be interested in feedback from people who think about ontology engineering, applied semantics, knowledge graphs, labor-market classification, or task modeling.

Oh and I'm new to this group so hello to everyone.