I think our problem space is complete
From an IT viewpoint, we can distinguish a finite number of elements, and classify them:
- A set of words, expressions to be turned in to a set of concepts, hopefully n..1
- Each concept can be grouped by the lexical class it impersonates (phrasing may be challenged)
- Corresponding concept as lemma, carrying lexical class as metadata and some first order semantics, followed by stemming preserving the lemma as main concept, forming a unique abstraction.
- This abstraction acting as a key, refers to collections of viewpoints, renderings (utterances or characters), definitions or formulas, to collections of revisions and collections of authors
It also refers to contexts as collection of first direct pa-rent(s) as abstractions, addressing inheritance, and to collection of other types of relations, fit to specify any application. Application, defining a container, its objects, and the relations that exist within, eventually links to outer world, is ontology. Note that every component, interlin-ked via abovementioned collections, is fully semantic, read 'linked to a world of synonyms and superclasses', facilitating knowledge discovery.
Abstraction as a key
Using abstractions in place of words implies that to every new word created, an abstraction must be created too, and added to the worldwide lexicon that results from this effort, via a gigantic web service.
For instance, Honda must register their new '2016 LX Honda Civic Blue 1.7L' so everyone worldwide refers to this model using corresponding abstraction. Updating the lexicon. This is the price to pay for being globally semantic.
Write Once, Use Everywhere...
An abstraction-based language-neutral represen-tation of digital assets eliminates multiple names for the same business object or process, a costly ailment common to IT departments in most corporations or federal agencies. Ultimately, applications may use FirstName, FIRST_NAME, or Nombre, but in the code, their abstraction, the same interoperable business object", acts as their proxy.
A word such as 'Employee' is stored as a sequence of letters E, m, p, l, o, y, e and e, which lets a human, English speaker, understand that it is related to an employer, an office, a mailing address or a salary.
For a computer, it is no more but this specific sequence of letters. Abstractions let computers 'understand' this word, and relate it to a nexus of concepts, going beyond RDF 1.1.
A huge task!
An individual can start up a pro-ject by himself. But if s/he succ-eeds in gathering people around it, and if there is a need, for such a project, even yet unmanifested, they may open-source
it and multiply resources.
In such a unified world, there are no such things as 'a foreign language'. One can always* find a term, an expression or a formula to define 'something' in a similar, or very close way, making them 'true' synonyms - cognates. I hear critics of this assertion...
'Synonym' here refers to all words written in all possible alphabets or formulations. The character 山
, is pronounced 'yama' in Japanese, and 'shan' in Chinese Mandarin, simplified or traditional.
*Some languages grant various hues of meaning to the same word or expression, but anyway, one can associate 'something' to this meaning, such as a description.
For instance, in Inu language (Inuktitut), there are dozens of 'words' to refer to snow and ice. Fifty-two to be precise. To any word or expression, the 'something' that I mentioned above associates an abstraction, which will serve as an umbrella for all synonyms, single vocable or expression, across other languages, to access one or more definitions (viewpoints).
may be described as 'speed x time', a formula, or by a literal definition. These are two viewpoints.