Asemantic triple, orRDF triple or simplytriple, is the atomic data entity in theResource Description Framework (RDF)data model.[1] As its name indicates, a triple is asequence of three entities that codifies astatement aboutsemantic data in the form of subject–predicate–object expressions (e.g., "Bob is 35", or "Bob knows John").
This format enablesknowledge to be represented in a machine-readable way. Particularly, every part of an RDF triple is individually addressable via uniqueURIs—for example, the statement "Bob knows John" might be represented in RDF as:
http://example.name#BobSmith12 http://xmlns.com/foaf/spec/#term_knows http://example.name#JohnDoe34.
Given this precise representation, semantic data can be unambiguouslyqueried andreasoned about.
The components of a triple, such as the statement "The sky has the color blue", consist of asubject ("the sky"), apredicate ("has the color"), and anobject ("blue"). This is similar to the classical notation of anentity–attribute–value model withinobject-oriented design, where this example would be expressed as an entity (sky), an attribute (color) and a value (blue).
From this basic structure, triples can be composed intomore complex models, by using triples as objects or subjects of other triples—for example,Mike → said → (triples → can be → objects).
Given their particular, consistent structure, a collection of triples is often stored in purpose-built databases calledtriplestores.
Arelational database is the classical form for information storage, working with different tables, which consist of rows. The query languageSQL is able to retrieve information from such a database. In contrast, RDF triple storage works with logical predicates. No tables nor rows are needed, but the information is stored in a text file. An RDF-triple store can be converted into an SQL database and the other way around.[2] If the knowledge is highlyunstructured and dedicated tables aren't flexible enough, semantic triples are used over classic relational storage.
In contrast to a traditional SQL database, an RDF triple store isn't created with a table editor. The preferred tool is aknowledge editor, for exampleProtégé.[3] Protégé looks similar to an object-oriented modeling application used forsoftware engineering, but it's focused on natural language information. The RDF triples are aggregated into aknowledge base, which allows external parsers to run requests. Possible applications include the creation of non-player characters within video games.[4]
One concern about triple storage is its lack ofdatabase scalability.[5] This problem is especially pertinent if millions of triples are stored and retrieved in a database. The seek time is larger than for classicalSQL-based databases.
A more complex issue is a knowledge model's inability to predict future states. Even if all the domain knowledge is available aslogical predicates, the model fails in answeringwhat-if questions. For example, suppose in the RDF format a room with a robot and table is described. The robot knows what the location of the table is, is aware of the distance to the table and knows also that a table is a type of furniture. Before the robot can plan its next action, it needstemporal reasoning capabilities.[6] Thus, the knowledge model should answer hypothetical questions in advance before an action is taken.
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