Re: abstract vs concrete concepts. upper ontolologies

If we take into consideration the fact that philosophy is characterized
generally by having five branches, that is (1) metaphysics, (2)
epistemology,  (3) logic, (4) ethics and (5) aesthetics we can conclude
that the abstract concepts can be categorized accordingly.

For completeness sake we can add philosophy of science, which roughly said
looks at how methodologies evolve and shape rational thinking and empirical
science.

Logic, linguistics and mathematics form the core to capture abstract
concepts in formal systems that lend themselves for computation, as is
obvious in LLMs.

But philosophy for practical purposes is a better organizing instrument for
knowledge representation,  exactly because it includes but is not identical
to epistemology.

And because language is the instrument of communication for philosophy,  we
are back to my premise to use semiotics,  symbol sets, pictograms,
(petro)glyphs and alphabets as the basis for abstraction.

Because empirical science generates (spectral) data, these must described
as well both quantitatively and qualitatively.

And because we are trying to create open, inclusive, accountable,
explainable,  trustworthy,  ethical and safe artificial intelligence that
is life-centric (not human-centric, but safe for all life on Earth), the
first four mentioned branches of philosophy form the basis for organizing
knowledge and its representation.

Of these four the first three have already been studied in extenso, it is
now only recently that ethics has joined the fray.

Again, I am working on producing several articles on both the organizing
instruments and formal systems for (abstract) knowledge representation.

I hope I have clarified my approach, I am a Godelian mathematician, which
means I acknowledge that universal theories of everything that are
consistent and complete do not exist, but we can construct formal systems
that can satisfy some requirements we may have for explaining empirical
data, and allow computation.

And since metaphysics,  epistemology,  logic and ethics cover pretty much
everything we want to capture in knowledge representation,  this should
suffice for all fields of human activity and Science, Technology,
Engineering and Mathematics in which we want to utilize artificial
intelligence.

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

On Fri, Jun 27, 2025, 09:36 Paola Di Maio <paola.dimaio@gmail.com> wrote:

>
> To understand why, in trying to capture the Knowledge Representation
> domain, which can be so elusive
> we start with upper/top level ontologies,
>
> There is a distinction between abstract vs concrete concepts
>
> The majority of words in English *check the other languages? *estimated
> around 70 percent, refer to abstract concepts
> These cannot be represented visually
> Yet, these abstract concepts convey essential meaning and semantics for
> concrete terms
> abstraction is essential to intelligent reasoning
>
> Upper Ontologies represent abstract categories require to add semantic
> dimensions to concrete terms and concepts
> PDM
>
>
> 1. Existence and Reality
>
> being / nonbeing
>
> existence / inexistence
>
> possibility / necessity
>
> actuality / potentiality
>
> ________________________________
>
> 2. Time
>
> duration
>
> moment / instant
>
> past / present / future
>
> frequency
>
> continuity / interruption
>
> ________________________________
>
> 3. Space and Place
>
> position / location
>
> distance / proximity
>
> direction
>
> extent / limit
>
> movement through space
>
> ________________________________
>
> 4. Quantity and Measurement
>
> number
>
> magnitude
>
> degree
>
> proportion
>
> comparison
>