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The Gellish Formal English Dictionary-Taxonomy (earlier called STEPlib) is an electronic 'smart' dictionary and taxonomy and ontology that contains definitions of concepts, each of which is identified by a unique identifier (UID) and can be referenced by one or more 'names' (terms, including synonyms, abbreviations and codes). Most of these are normal English terms, many of them can also be found in ordinary English dictionaries. All definitions satisfy the rules for proper definitions of concepts in Gellish Formal English. This means that they not only have a textual definition, but also that they have at least an explicit relation with their supertype concept(s) and thus form a consistent subtype-supertype hierarchy of concepts or Taxonomy. The Gellish Modeling Method provides guidelines for the extension of the dictionary-taxonomy such as with Domain Dictionaries for specialized areas and for the creation of Dictionaries-Taxonomies in other languages. Such other dictionaries enable automated translation of expressions, provided that the common unique identifiers are used.
The Gellish Formal English Dictionary-Taxonomy 2008 version is free of charge available under Open Source conditions (through an Open Source License) via this website. Later versions and proprietary extensions are available for licensees or can be purchased via the webshop.
An essential section (domain) of the definitions in the Gellish Formal English Dictionary-Taxonomy are the definitions of relation types. Relation types typically have 'phrases' as names, which phrases that can be used in Gellish Formal English expressions. For example a composition relation has as name 'is a part of', which phrase can be used in a Gellish expression such as: A is a part of B. So the Gellish dictionary does not provide a definition of the separate words, like is, a, part and of, but it gives a definition of the whole phrase, because the phrase represents a concept. The section of the Gellish Dictionary-Taxonomy that contains the collection of upper ontological facts (TOPini) contains the definition of the standard relation types of Gellish. They currently have 'names' and 'Gellish phrases' in English and in Dutch (Nederlands). That part also contains definitions of the kinds of the roles that are played by objects in relations of those types and it contains definitions of the types of things that can play such roles. The definitions of relation types also satisfy the rules for proper definitions of concepts in Gellish English and thus form a consistent subtype-supertype hierarchy of relation types. As all concepts in the Gellish English Dictonary, including the relation types, roles and other kinds of things, are arranged in a subtype-supertype hierarchy of concepts, the Gellish Dictionary is also a Taxonomy. The collection of upper ontological facts (TOPini) in the dictionary forms the top of that subtype-supertype hierarchy of concepts. All other concepts in the dictionary are subtypes of the generic concepts. The data in the Gellish English Dictionary are stored in a Gellish Database of Message File, as defined in the document 'Definition of Universal Semantic Databases and Data Exchange Message'.
The Gellish English Dictionary-Taxonomy defines concepts by expressing computer interpretable facts about the concepts. The prime expressions have the form of specialization relations or qualification relations. The facts are grouped in collections of facts that define domain specific subsets of the dictionary. In the current Gellish English Dictionary collections of facts can be distinguished about the following domains:
Every concept is a subtype of a more generic concept, up to the top concept, called anything.
Lower in the hierarchy you will find the more specialized concepts as defined in engineering standards and in proprietary standards. Further specialized concepts, such as catalog items and manufacturer's models are again subtypes of more generalized concepts.
A smart dictionary has a number of characteristics in addition to ordinary dictionaries.
The Gellish Formal English Dictionary-Taxonomy is an electronic smart dictionary because it satisfies the following rules for smart dictionaries:
The fact that the Gellish Formal English Dictionary satisfies this rule means that the Gellish Dictionary itself defines the Gellish Formal English language. In Gellish Formal English those relation types have names and synonyms that consist of standardized phrases. For example: the phrase 'is a part of' can be used to express the fact that A is a part of B, whereas the phrase 'can have as part a' can be used to express the knowledge that a whole of a particular kind can have as part a component of a particular kind. For example, the fact that a pump can have a bearing is expressed in Gellish Formal English as:
pump can have as part a bearing.
All three elements in this expression are names of standard Gellish English concepts that are defined in the Gellish English Dictionary.
The Gellish dictionary contains a special collection of facts that specify how expressions of knowledge can be used to create expressions of real facts about individual things.
These are <can be realized by a> relations. Each relation of that kind relates two kinds of relations:
with
An example of such a relation is the expression of the fact that:
The collection of such relations in the Gellish Smart Dictionary specify which kind of relation type should be used when knowledge or requirements are used to create facts about individual things in an imaginary or real world. This is typically used when knowledge or requirements are turned into designs.
The following example illustrates the basic principles of knowledge-based design using Gellish. Assume that a requirement expresses that
The above-mentioned Gellish language relations define how to apply that knowledge to create bearings for individual pumps. For example, assume that P-101 is classified as a pump, then software that is Gellish English powered can conclude that
whereas
Such software can also derive from the Gellish Dictionary what kinds of bearings there are and from a knowledge model in Gellish it can derive which characteristics such components normally have.
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