Gellish English dictionary

• It contains definitions per concept, each represented by a unique identifier, whereas ordinary dictionaries usually provide multiple different definitions of a single term, whereas it is unclear whether those definitions are alternative definitions of the same concept or whether they are definitions of different concepts. Thus a smart dictionary explicitly distinguishes homonyms and explicitly specifies which terms are used as true synonyms, including also abbreviations, codes, etc.
• It is defined itself in the form of a Gellish Data Tables that form a Gellish Database.
• It is completely arranged as a taxonomy, which is a subtype-supertype hierarchy of concepts. This means that each concept is defined as an explicit subtype of one or more supertype concepts by specialization relations. This enables inheritance of definitions, knowledge, and requirements. An example of some definitions and hierarchy is the following:

• It includes also concepts with multi-term names. For example: line shaft centrifugal pump. Ordinary dictionaries will only define the separate terms, from which it cannot always be inferred what the multi-term means.
• It defines kinds of relations, also called relation types or fact types, as being special kinds of concepts. Such kinds of facts do not appear in ordinary dictionaries, because they are word-based and do not recognize standard phrases. However, fact types represent semantic concepts that are used by everybody to make sentences. Because these relation types are standardized and unambiguously defined, Gellish English becomes computer interpretable. The relation types in the dictionary-taxonomy include kinds that are specific for the expression of facts that represent knowledge, requirements, definitions, and information about individual things. The relation types have names and synonyms that consist of standardized phrases. For example :

• It includes explicit relations between concepts, using the above mentioned standardized relation types. Those relations express knowledge about the concepts. This means that the dictionary-taxonomy is also an ontology. If a user of an application system classifies an individual object by a concept in the dictionary-taxonomy, then a computer system can infer that the knowledge and requirements about the concept are applicable to that individual object, and it can make that information available to that user. This includes also the knowledge and requirements that are available about the supertypes of that concepts, because such knowledge and requirements are inherited by the subtype of those supertype concepts, conforming to the subtype-supertype hierarchy.
• It enables automatic translation and search in databases in other languages. This is possible because each concept is represented by a language-independent UID, whereas multiple terms in various languages are allowed to denote the same concept. This makes it possible for facts that are expressed in one language to be automatically presented by a computer in any other language for which a smart dictionary is available. It also makes it possible to answer queries in one language using database systems that contain facts that are expressed in other languages and then present the results in the language in which the query was formulated.
• It can be extended by private and proprietary concepts and terms. For example, company specific codes and proprietary knowledge can be added as required. Guidelines for the "proper definition of a concept" are provided in the documentation.
• It is computer interpretable and system independent.