Cyc Ontology
A Cyc Ontology is an ontology produced by the Cyc project.
- AKA: Cyc KB, Cyc Knowledge Base.
- Context:
- It can range from (typically) being a Cyc Upper Ontology to being a Cyc Middle Ontology to being a Cyc Bottom Ontology.
- See: Cyc Microtheory, Cyc Lexicon.
References
2017
- (CYC, 2017) ⇒ "Knowledge Base" Retrieved 2017-01-08 http://www.cyc.com/kb/
- The Cyc Knowledge Base is so large that it can seem unwieldy and difficult to navigate at first glance.
The Cyc Knowledge Base (KB) is a formalized representation of a vast quantity of fundamental human knowledge: facts, rules of thumb, and heuristics for reasoning about the objects and events of everyday life. This knowledge is represented in a formal language, CycL. The KB consists of terms and assertions which relate those terms. These assertions include both simple facts (i.e., ground assertions) and rules. The Cyc KB is divided into many (currently thousands of) “contexts” (or “microtheories”), each of which is essentially a collection of assertions that share a common set of assumptions; some microtheories are focused on a particular domain of knowledge, some a particular interval in time, some a particular level of detail, etc. The microtheory mechanism allows Cyc to independently maintain assertions which are prima facie contradictory, and enhances the performance of the Cyc system by focusing the inferencing process. At the present time, the Cyc KB contains over five hundred thousand terms, including about seventeen thousand types of relations, and about seven million assertions relating these terms. New assertions are continually added to the KB through a combination of automated and manual means. Many more concepts can be expressed functionally, thereby enabling the automatic creation of millions of non-atomic terms, such as (LiquidFn Nitrogen) being used to describe liquid nitrogen. Additionally, Cyc adds a vast number of assertions to the KB by itself as a result of the inferencing process.
- The Cyc Knowledge Base is so large that it can seem unwieldy and difficult to navigate at first glance.
2013
- (Wikipedia, 2013) ⇒ http://en.wikipedia.org/wiki/Cyc#Knowledge_base
- QUOTE: The concept names in Cyc are known as constants. Constants start with an optional "#$" and are case-sensitive. There are constants for: * Individual items known as individuals, such as #$BillClinton or #$France. * Collections, such as #$Tree-ThePlant (containing all trees) or #$EquivalenceRelation (containing all equivalence relations). A member of a collection is called an instance of that collection. * Truth Functions which can be applied to one or more other concepts and return either true or false. For example #$siblings is the sibling relationship, true if the two arguments are siblings. By convention, truth function constants start with a lower-case letter. Truth functions may be broken down into logical connectives (such as #$and, #$or, #$not, #$implies), quantifiers (#$forAll, #$thereExists, etc.) and predicates. * Functions, which produce new terms from given ones. For example, #$FruitFn, when provided with an argument describing a type (or collection) of plants, will return the collection of its fruits. By convention, function constants start with an upper-case letter and end with the string "Fn".
The most important predicates are #$isa and #$genls. The first one describes that one item is an instance of some collection, the second one that one collection is a subcollection of another one. Facts about concepts are asserted using certain CycL sentences. Predicates are written before their arguments, in parentheses:
(#$isa #$BillClinton #$UnitedStatesPresident)"Bill Clinton belongs to the collection of U.S. presidents" and(#$genls #$Tree-ThePlant #$Plant)"All trees are plants".(#$capitalCity #$France #$Paris)"Paris is the capital of France."Sentences can also contain variables, strings starting with "?". These sentences are called "rules". One important rule asserted about the #$isa predicate reads
(#$implies (#$and (#$isa ?OBJ ?SUBSET) (#$genls ?SUBSET ?SUPERSET)) (#$isa ?OBJ ?SUPERSET))with the interpretation "if OBJ is an instance of the collection SUBSET and SUBSET is a subcollection of SUPERSET, then OBJ is an instance of the collection SUPERSET". Another typical example is(#$relationAllExists #$biologicalMother #$ChordataPhylum #$FemaleAnimal)which means that for every instance of the collection #$ChordataPhylum (i.e. for every chordate), there exists a female animal (instance of #$FemaleAnimal) which is its mother (described by the predicate #$biologicalMother).The knowledge base is divided into microtheories (Mt), collections of concepts and facts typically pertaining to one particular realm of knowledge. Unlike the knowledge base as a whole, each microtheory is required to be free from contradictions. Each microtheory has a name which is a regular constant; microtheory constants contain the string "Mt" by convention. An example is #$MathMt, the microtheory containing mathematical knowledge. The microtheories can inherit from each other and are organized in a hierarchy: one specialization of #$MathMt is #$GeometryGMt, the microtheory about geometry.
- QUOTE: The concept names in Cyc are known as constants. Constants start with an optional "#$" and are case-sensitive. There are constants for: * Individual items known as individuals, such as #$BillClinton or #$France. * Collections, such as #$Tree-ThePlant (containing all trees) or #$EquivalenceRelation (containing all equivalence relations). A member of a collection is called an instance of that collection. * Truth Functions which can be applied to one or more other concepts and return either true or false. For example #$siblings is the sibling relationship, true if the two arguments are siblings. By convention, truth function constants start with a lower-case letter. Truth functions may be broken down into logical connectives (such as #$and, #$or, #$not, #$implies), quantifiers (#$forAll, #$thereExists, etc.) and predicates. * Functions, which produce new terms from given ones. For example, #$FruitFn, when provided with an argument describing a type (or collection) of plants, will return the collection of its fruits. By convention, function constants start with an upper-case letter and end with the string "Fn".
2007
- (Obitko, 2007) ⇒ Marek Obitko. (2007). “Translations Between Ontologies in Multi-agent Systems - Ontology Operations].” PhD Thesis, Czech Technical University http://www.obitko.com/tutorials/ontologies-semantic-web/body-of-knowledge.html
- The typical example is the project CYC that defines its knowledge base as an ontology for any other knowledge based system. CYC is the name of a very large, multi-contextual knowledge base and inference engine. CYC is an early attempt to do symbolic AI on a massive scale by capturing common knowledge that is required to do tasks that are trivial for people, but very hard for computers. All of the knowledge in CYC is represented declaratively in the form of logical assertions. CYC contains over 400,000 significant assertions, which include simple statements of facts, rules about what conclusions to draw if certain statements of facts are satisfied, and rules about how to reason with certain types of facts and rules. New conclusions are derived by the inference engine using deductive reasoning. The CYC common sense knowledge can be used as a foundation of a knowledge base for any knowledge intensive system. In this sense, this body of knowledge can be viewed as an ontology of the knowledge base of the system.
2005
- (Ramachandran et al., 2005) ⇒ Deepak Ramachandran, Pace Reagan, and Keith Goolsbey. (2005). “First-orderized Researchcyc: Expressivity and Efficiency in a Common-sense Ontology.” In: AAAI Workshop on Contexts and Ontologies: Theory, Practice and Applications.
- QUOTE: Cyc is the largest existing common sense knowledge base. Its ontology makes heavy use of higher-order logic constructs such as a context system, first class predicates, etc. Many of these higher-order constructs are believed to be key to Cyc’s ability to represent common sense knowledge and reason with it efficiently.