Re: abstract vs concrete concepts. upper ontolologies

Owen, and all
I can see that the notion of knowledge representation is not sinking in
easily
It has always been the case
I hope that once we have a good model it can be uploaded directly onto
brains :-)
PDM


On Sat, Jun 28, 2025 at 12:02 AM Owen Ambur <owen.ambur@verizon.net> wrote:

> How's this -- A Practical Plan to Apply the Logic of Philosophy to AI
> <https://stratml.us/docs/PCoR.xml> -- for a non sequitur?
>
> If there's interest in fleshing out the plan with performance indicators
> and stakeholder roles, ChatGPT stands ready
> <https://chatgpt.com/share/685ebfef-10fc-800b-b464-b5138211eacc> to help
> us do so.
>
> Owen Ambur
> https://www.linkedin.com/in/owenambur/
>
>
> On Friday, June 27, 2025 at 10:47:06 AM EDT, Milton Ponson <
> rwiciamsd@gmail.com> wrote:
>
>
> 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
>
>