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This document presents a framework for specifying the semantics for the languages of the Semantic Web. Some of these languages (notably RDF [RDFPRIMER] [RDFVOCABULARY] [RDFSYNTAX] [RDFCONCEPTS] [RDFSEMANTICS], and OWL [OWL]) are currently in various stages of development and we expect others to be developed in the future. This framework is intended to provide a framework for specifying the semantics of all of these languages in a uniform and coherent way. The strategy is to translate the various languages into a common 'base' language thereby providing them with a single coherent model theory.
We describe a mechanism for providing a precise semantics for the Semantic Web Languages (referred to as SWELs from now on. The purpose of this is to define clearly the consequences and allowed inferences from constructs in these languages.
This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C Recommendations and other technical reports is available at http://www.w3.org/TR/.
This document is a W3C NOTE for the use by W3C Members and other interested parties. It may be updated, replaced or made obsolete by other documents at any time.
This document results from discussions within the RDF Core Working Group concerning the formalization of RDF and RDFbased languages. The RDF Core Working Group is part of the W3C Semantic Web Activity. The group's goals and requirements are discussed in the RDF Core Working Group charter. These include requirements that...
This document is motivated by these two requirements. It does not present an RDF Core WG design for Semantic Web layering. Rather, it documents a technique that the RDF Core WG are using in our discussions and in the RDF Semantics specification. The RDF Core WG solicit feedback from other Working Groups and from the RDF implementor community on the wider applicability of this technique.
Note that the use of the abbreviation "SWEL" in Lbase differs from the prior use of "SWeLL" in the MIT/LCS DAML project.
In conformance with W3C policy requirements, known patent and IPR constraints associated with this Note are detailed on the RDF Core Working Group Patent Disclosure page.
Review comments on this document are invited and should be sent to the public mailing list wwwrdfcomments@w3.org. An archive of comments is available at http://lists.w3.org/Archives/Public/wwwrdfcomments/.
Discussion of this document is invited on the wwwrdflogic@w3.org list of the RDF Interest Group (public archives).
A modeltheoretic semantics for a language assumes that the language refers to a 'world', and describes the minimal conditions that a world must satisfy in order to assign an appropriate meaning for every expression in the language. A particular world is called an interpretation, so that model theory might be better called 'interpretation theory'. The idea is to provide a mathematical account of the properties that any such interpretation must have, making as few assumptions as possible about its actual nature or intrinsic structure. Model theory tries to be metaphysically and ontologically neutral. It is typically couched in the language of set theory simply because that is the normal language of mathematics  for example, this semantics assumes that names denote things in a set IR called the 'universe'  but the use of settheoretic language here is not supposed to imply that the things in the universe are settheoretic in nature.
The chief utility of such a semantic theory is not to suggest any particular processing model, or to provide any deep analysis of the nature of the things being described by the language, but rather to provide a technical tool to analyze the semantic properties of proposed operations on the language; in particular, to provide a way to determine when they preserve meaning. Any proposed inference rule, for example, can be checked to see if it is valid with respect to a model theory, i.e. if its conclusions are always true in any interpretation which makes its antecedents true.
We note that the word 'model' is often used in a rather different sense, eg as in 'data model', to refer to a computational system or data structures of some kind. To avoid misunderstanding, we emphasise that the interpretations referred to in a model theory are not, in general, intended to be thought of as things that can be computed or manipulated by computers.
There will be many Semantic Web languages, most of which will be built on top of more basic Semantic Web language(s). It is important that this layering be clean and simple, not just for human understandability, but also to enable the construction of robust semantic web agents that use these languages. The emerging current practice is for each of the SWELs to be defined in terms of their own model theory, layering it on top of the model theories of the languages they are layered upon. While having a model theory is clearly desireable, and even essential, for a SWEL, this directconstruction approach has several problems. It produces a range of model theories, each with its own notion of consequence and entailment. It requires expertise in logic to make sure that model theories align properly, and modeltheoretic alignment does not always sit naturally with interoperability requirements. Experience to date (particularly with the OWL standard under development at the time of writing by the W3C Webont working group) shows that quite difficult problems can arise when layering model theories for extensions to the 'basic' RDF layer [RDF] of the semantic web. Moreover, this strategy places a very high burden on the 'basic' layer, since it is difficult to anticipate the semantic demands which will be made by all future higher layers, and the expectations of different development and user communities may conflict. Further, we believe that a melange of model theories will adversely impact developers building agents that implement proof systems for these layers, since the proof systems will likely be different for each layer, resulting in the need to micromanage small semantic variations for various dialects and sublanguages (cf. the distinctions between various dialects of OWL).
In this document, we use an alternative approach to for defining the semantics for the different SWELs in a fashion which ensures interoperability. We first define a basic language L_{base} which is expressive enough to state the content of all currently proposed web languages, and has a fixed, clear modeltheoretic semantics. Then, the semantics of each SWEL L_{i} is defined by specifying how expressions in the L_{i} map into equivalent expressions in L_{base}, and by providing axioms written in L_{base} which constrain the intended meanings of the SWEL special vocabulary. The L_{base} meaning of any expression in any SWEL language can then be determined by mapping it into L_{base} and adding the appropriate language axioms, if there are any.
The intended result is that the model theory of L_{base} is the model theory of all the Semantic Web Languages, even though the languages themselves are different. This makes it possible to use a single inference mechanism to work on these different languages. Although it will possible to exploit restrictions on the languages to provide better performance, the existence of a reference proof system is likely to be of utility to developers. This also allows the meanings of expressions in different SWELs to be compared and combined, which is very difficult when they all have distinct model theories.
The idea of providing a semantics for SWELs by translating them into logic is not new [see for example Marchiolri&Saarela, Fikes&McGuinness] but we plan to adopt a somewhat different style than previous 'axiomatic semantics', which have usually operated by mapping all RDF triples to instances of a single threeplace predicate. We propose rather to use the logical form of the target language as an explication of the intended meaning of the SWEL, rather than simply as an axiomatic description of that meaning, so that RDF classes translate to unary predicates, RDF properties to binary relations, the relation rdf:type translates to application of a predicate to an argument, and listvalued properties in OWL or DAML can be translated into nary or variadic relations. The syntax and semantics of L_{base} have been designed with this kind of translation in mind. It is our intent that the model theory of L_{base} be used in the spirit of its model theory and not as a programming language, i.e., relations in L_{i} should correspond to relations in L_{base}, variables should correspond to variables and so on.
It is important to note that L_{base} is not being proposed as a SWEL. It is a tool for specifying the semantics of different SWELs. The syntax of L_{base} described here is not intended to be accessible for machine processing; any such proposal should be considered to be a proposal for a more expressive SWEL.
By using a well understood logic (i.e., first order logic [Enderton]) as the core of L_{base}, and providing for mutually consistent mappings of different SWELs into L_{base}, we ensure that the content expressed in several SWELs can be combined consistently, avoiding paradoxes and other problems. Mapping type/class language into predicate/application language also ensures that settheoretical paradoxes do not arise. Although the use of this technique does not in itself guarantee that mappings between the syntax of different SWELs will always be consistent, it does provide a general framework for detecting and identifying potential inconsistencies.
It is also important that the axioms defining the vocabulary items introduced by a SWEL are internally consistent. Although firstorder logic (and hence L_{base}) is only semidecideable, we are confident that it will be routine to construct L_{base} interpretations which establish the relevant consistencies for all the SWELs currently contemplated. In the general case, future efforts may have to rely on certifications from particular automated theorem provers stating that they weren't able to find an inconsistency with certain stated levels of effort. The availablity of powerful inference engines for firstorder logic is of course relevant here.
In this document, we use a version of first order logic with equality as L_{base}. This imposes a fairly strict monotonic discipline on the language, so that it cannot express local default preferences and several other commonlyused nonmonotonic constructs. We expect that as the Semantic Web grows to encompass more and our understanding of the Semantic Web improves, we will need to replace this L_{base} with more expressive logics. However, we expect that first order logic will be a proper subset of such systems and hence we will be able to smoothly transition to more expressive L_{base} languages in the future. We note that the computational advantages claimed for various sublanguages of firstorder logic, such as description logics, logical programming languages and frame languages, are irrelevant for the purposes of using L_{base} as a semantic specification language.
We will use First Order Logic with suitable minor changes to account for the use of referring expressions (such as URIs) on the Web, and a few simple extensions to improve utility for the intended purposes.
Any firstorder logic is based on a set of atomic terms, which are used as the basic referring expressions in the syntax. These include names, which refer to entities in the domain, special names, and variables. L_{base} allows character strings (not starting with the characters ')','(', '\', '?','<' or ''' , and containing no whitespace characters) as names, but distinguishes the special class of urirefs, defined to be a URI reference in the sense of [URI]. Urirefs are used to refer to both individuals and relations between the individuals.
L_{base} allows for various collections of special names with fixed meanings defined by other specifications (external to the L_{base} specification). There is no assumption that these could be defined by collections of L_{base} axioms, so that imposing the intended meanings on these special names may go beyond strict firstorder expressiveness. (In mathematical terms, we allow that some sets of names refer to elements of certain fixed algebras, even when the algebra has no characteristic firstorder description.) Each such set of names has an associated predicate which is true of the things denoted by the names in the set. At present, we assume three categories of such fixed names: numerals, quoted strings, and XML structures, with associated predicate names 'NatNumber', 'String', and 'XmlThing' respectively.
Numerals are defined to be strings of the characters '0123456789', and are interpreted as decimal numerals in the usual way. Since arithmetic is not firstorder definable, this is the first and most obvious place that L_{base} goes beyond firstorder expressiveness.
Quoted strings are arbitrary character sequences enclosed in (single) quotation marks, and are interpreted as denoting the string inside the quotation marks. The backslash character is used as a selfescaping prefix escape to include a quote mark in a quoted string. Quoted strings denote the strings they contain, i.e. any such string denotes the string gotten by removing the two surrounding quote marks and unescaping any inner quote marks which are then at the beginning or end. For example,
'\'a\\\'b\''
is a quoted string which denotes the string:
'a\\\'b'
Double quote marks have no special interpretation.
An XML structure is a character string which is a wellformed piece of XML, possibly with an XML lang tag, and it is taken to denote an abstract structure representing the parsed XML with the lang tag attached to any enclosed literals.
The associated predicate names NatNumber, String, XmlThing and Relation (see below) are considered to be special names.
A variable is any nonwhitespace character string starting with the character '?'.
The characters '(', ',' and ')' are considered to be punctuation symbols.
The categories of punctuation, whitespace, names, special names and variables are exclusive and each such string can be classified by examining its first character. This is not strictly necessary but is a useful convention.
Any L_{base} language is defined with respect to a vocabulary, which is a set of nonspecial names. We require that every L_{base} vocabulary contain all urirefs, but other expressions are allowed. (We will require that every L_{base} interpretation provide a meaning for every special name, but these interpretations are fixed, so special names are not counted as part of the vocabulary.)
There are several aspects of meaning of expressions on the semantic web which are not yet treated by this semantics; in particular, it treats URIs as simple names, ignoring aspects of meaning encoded in particular URI forms [RFC 2396] and does not provide any analysis of timevarying data or of changes to URI denotations. The model theory also has nothing to say about whether an HTTP uri such as "http://www.w3.org/" denotes the World Wide Web Consortium or the HTML page accessible at that URI or the web site accessible via that URI. These complexities may be addressed in future extensions of L_{base}; in general, we expect that L_{base} will be extended both notationally and by adding axioms in order to track future standardization efforts.
We do not take any position here on the way that urirefs may be composed from other expressions, e.g. from relative URIs or Qnames; the model theory simply assumes that such lexical issues have been resolved in some way that is globally coherent, so that a single uriref can be taken to have the same meaning wherever it occurs.
Similarly, the model theory given here has no special provision for tracking temporal changes. It assumes, implicitly, that urirefs have the same meaning whenever they occur. To provide an adequate semantics which would be sensitive to temporal changes is a research problem which is beyond the scope of this document..
We will assume that there are three sets of names (not special names) which together constitute the vocabulary: individual names, relation names, and function names, and that each function name has an associated arity, which is a nonnegative integer. In a particular vocabulary these sets may or may not be disjoint. Expressions in L_{base} (speaking strictly, L_{base} expressions in this particular vocabulary) are then constructed recursively as follows:
A term is either a name or a special name or a variable, or else it has the form f(t1,...,tn) where f is an nary function name and t1,...,tn are terms.
A formula is either atomic or boolean or quantified, where:
an atomic formula has the form (t1=t2) where t1 and t2 are terms, or else the form R(t1,...,tn) where R is a relation name or a variable and t1,...,tn are terms;
a boolean formula has one of the forms
(W1 and W2 and ....and Wn)
(W1 or W2 or ... or Wn)
(W1 implies W2)
(W1 iff W2)
(not W1)
where W1, ...,Wn are formulae; and
a quantified formula has one of the forms
(forall (?v1 ...?vn) W)
(exists (?v1 ... ?vn) W)
where ?v1,...,?vn are variables and W is a formula. (The subexpression just after the quantifier is the variable list of the quantifier. Any occurrence of a variable in W is said to be bound in the quantified formula by the nearest quantifer to the occurrence which includes that variable in its variable list, if there is one; otherwise it is said to be free in the formula.)
Finally, an L_{base} knowledge base is a set of formulae.
Formulae are also called 'wellformed formulae' or 'wffs' or simply 'expressions'. In general, surplus brackets may be omitted from expressions when no syntactic ambiguity would arise.
Some comments may be in order. The only parts of this definition which are in any way nonstandard are (1) allowing 'special names', which was discussed earlier; (2) allowing variables to occur in relation position, which might seem to be at odds with the claim that L_{base} is firstorder  we discuss this further below  and (3) not assigning a fixed arity to relation names. This last is a useful generalization which makes no substantial changes to the usual semantic properties of firstorder logic, but which eases the translation process for some SWEL syntactic constructs. (The computational properties of such 'variadic relations' are quite complex, but L_{base} is not being proposed as a language for computational use.)
The following definition of an interpretation is couched in mathematical language, but what it amounts to intuitively is that an interpretation provides just enough information about a possible way the world might be  a 'possible world'  in order to fix the truthvalue (true or false) of any L_{base} well formed formula in that world. It does this by specifying for each uriref, what it is supposed to be a name of; and also, if it is a function symbol, what values the function has for each choice of arguments; and further, if it is a relation symbol, which sequences of things the relation holds between. This is just enough information to determine the truthvalues of all atomic formulas; and then this, together with a set of recursive rules, is enough to assign a truth value for any L_{base} formula.
In specifying the following it is convenient to define use some standard definitions. A relation over a set S is a set of finite sequences (tuples) of members of S. If R is a relation and all the elements of R have the same length n, then R is said to have arity n, or to be a nary relation. Not every relation need have an arity. If R is an (n+1)ary relation over S which has the property that for any sequence <s1,...,sn> of members of S, there is exactly one element of R of the form <s0, s1, ..., sn>, then R is an nary function; and s0 is the value of the function for the arguments s1, ...sn. (Note that an nary function is an (n+1)ary relation, and that, by convention, the function value is the first argument of the relation, so that for any nary function f, f(y,x1,...,xn) means the same as y = f(x1,...,xn).)
The conventional textbook treatment of firstorder interpretations assumes that relation symbols denote relations. We will modify this slightly to require that relation symbols denote entities with an associated relation, called the relational extension, and will sometimes abuse terminology by referring to the entities with relational extensions as relations. This device gives L_{base} some of the freedom to quantify over relations which would be familiar in a higherorder logic, while remaining strictly a firstorder language in its semantic and metatheoretic properties. We will use the special name Relation to denote the property of having a relational extension.
Let VV be the set of all variables, and NN be the set of all special names.
We will assume that there is a globally fixed mapping SN from elements of NN to a domain ISN (i.e, consisting of character strings, integers and XML structures). The exact specification of SN is given for numerals by the usual reading of a decimal numeral to denote a natural number; for quoted strings by the dequotation rules described earlier; and for XML structures by the XML 1.0 specification [XML].
An interpretation I of a vocabulary V is then a structure defined by:
which satisfies the following conditions:
An interpretation then specifies the value of any other L_{base} expression E according to the following rules:
if E is:  then I(E) is: 
a name or a variable  IS(E) 
a special name  SN(E) 
a term f(t1,...,tn)  the value of IEXT(I(f)) for the arguments I(t1),...,I(tn) 
an equation (A=B)  true if I(A)=I(B), otherwise false 
a formula of the form R(t1,...,t2)  true if IEXT(I(R)) contains the sequence <I(t1),...,I(tn)>, otherwise false 
(W1 and ...and Wn)  true if I(Wi)=true for i=1 through n, otherwise false 
(W1 or ...or Wn)  false if I(Wi)=false for i=1 through n, otherwise true 
(W1 <=> W2)  true if I(W1)=I(W2), otherwise false 
(W1 => W2)  false if I(W1)=true and I(W2)=false, otherwise true 
not W  true if I(W)=false, otherwise false 
If B is a mapping from a set W of variables into ID, then define [I+B] to be the interpretation which is like I except that [I+B](?v)=B(?v) for any variable ?v in W.
if E is:  then I(E) is: 
(forall (?v1,...,?vn) W)  false if [I+B](W)=false for some mapping B from {?v1,...,?vn} into ID, otherwise true 
(exist (?v1,...,?vn) W)  true if [I+B](W)=true for some mapping B from {?v1,...,?vn} into ID, otherwise false 
Intuitively, the meaning of an expression containing free variables is not well specified (it is formally specified, but the interpretation of the free variables is arbitrary.) To resolve any confusion, we impose a familiar convention by which any free variables in a sentence of a knowledge base are considered to be universally quantified at the top level of the expression in which they occur. (Equivalently, one could insist that all variables in any knowledgebase expression be bound by a quantifier in that expression; this would force the implicit quantification to be made explicit.)
These definitions are quite conventional. The only unusual features are the incorporation of specialname values into the domain, the use of an explicit extension mapping, the fact that relations are not required to have a fixed arity, and the description of functions as a class of relations.
The explicit extension mapping is a technical device to allow relations to be applied to other relations without going outside firstorder expressivity. We note that while this allows the same name to be used in both an individual and a relation position, and in a sense gives relations (and hence functions) a 'firstclass' status, it does not incorporate any comprehension principles or make any logical assumptions about what relations are in the domain. Notice that no special semantic conditions were invoked to treat variables in relation position differently from other variables. In particular, the language makes no comprehension assumptions whatever. The resulting language is firstorder in all the usual senses: it is compact and satisfies the downward SkolemLowenheim property, for example, and the usual machineoriented inference processes still apply, in particular the unification algorithm. (One can obtain a translation into a more conventional syntax by rewriting every atomic sentence using a rule of the form R(t1,...,tn) => Holds(R, t1,...,tn), where 'Holds' is a 'dummy' relation indicating that the relation R is true of the remaining arguments. The presentation given here eliminates the need for this artificial translation, but its existence establishes the firstorder properties of the language. To translate a conventional firstorder syntax into the L_{base} form, simply qualify all quantifiers to range only over nonRelations. The issue is further discussed in (Hayes & Menzel ref). )
Allowing relations with no fixed arity is a technical convenience which allows L_{base} to accept more natural translations from some SWELs. It makes no significant difference to the metatheory of the formalism compared to a fixedarity sytnax where each relation has a given arity. Treating functions as a particular kind of relation allows us to use a function symbol in a relation position (albeit with a fixed arity, which is one more than its arity as a function); this enables some of the translations to be specified more efficiently.
As noted earlier, incorporating special name interpretations (in particular, integers) into the domain takes L_{base} outside strict firstorder compliance, but these domains have natural recursive definitions and are in common use throughout computer science. Mechanical inference systems typically have specialpurpose reasoners which can effectively test for satisfiability in these domains. Notice that the incorporation of these special domains into an interpretation does not automatically incorporate all truths of a full theory of such structures into L_{base}; for example, the presence of the integers in the semantic domain does not in itself require all truths of arithmetic to be valid or provable in L_{base}.
An axiom scheme stands for an infinite set of L_{base} sentences all having a similar 'form'. We will allow schemes which are like L_{base} formulae except that expressions of the form "<exp1>...<expn>", ie two expressions of the same syntactic category separated by three dots, can be used, and such a schema is intended to stand for the infinite knowledge base containing all the L_{base} formulae gotten by substituting some actual sequence of appropriate expressions (terms or variables or formulae) for the expression shown, which we call the L_{base} instances of the scheme. (We have in fact been using this convention already, but informally; now we are making it formal.) For example, the following is an L_{base} scheme:
(forall (?v1...?vn)(R(?v1...?vn) implies Q(a, ?v2...?vn)))
 where the expression after the first quantifier is an actual scheme expression, not a conventional abbreviation  which has the following L_{base} instances, among others:
(forall (?x)(R(?x) implies Q(a, ?x)))
(forall (?y,?yy,?z)(R(?y, ?yy, ?z) implies Q(a,?y,?yy,?z)))
Axiom schemes do not take the language beyond firstorder, since all the instances are firstorder sentences and the language is compact, so if any L_{base} sentence follows from (the infinite set of instances of) an axiom scheme, then it must in fact be entailed by some finite set of instances of that scheme.
We note that L_{base} schemes should be understood only as syntactic abbreviations for (infinite) sets of L_{base} sentences when stating translation rules and specifying axiom sets. Since all L_{base} expressions are required to be finite, one should not think of L_{base} schemes as themselves being sentences; for example as making assertions, as being instances or subexpressions of L_{base} sentences, or as being posed as theorems to be proved. Such usages would go beyond the firstorder L_{base} framework. (They amount to a convention for using infinitary logic: see [Hayes& Menzel] for details.) This kind of restricted use of 'axiom schemes' is familiar in many textbook presentations of logic.
Following conventional terminology, we say that I satisfies E if I(E)=true, and that a set S of expressions entails E if every interpretation which satisfies every member of S also satisfies E. If the set S contains schemes, they are understood to stand for the infinite sets of all their instances. Entailment is the key idea which connects modeltheoretic semantics to realworld applications. As noted earlier, making an assertion amounts to claiming that the world is an interpretation which assigns the value true to the assertion. If A entails B, then any interpretation that makes A true also makes B true, so that an assertion of A already contains the same "meaning" as an assertion of B; we could say that the meaning of B is somehow contained in, or subsumed by, that of A. If A and B entail each other, then they both "mean" the same thing, in the sense that asserting either of them makes the same claim about the world. The interest of this observation arises most vividly when A and B are different expressions, since then the relation of entailment is exactly the appropriate semantic licence to justify an application inferring or generating one of them from the other. Through the notions of satisfaction, entailment and validity, formal semantics gives a rigorous definition to a notion of "meaning" that can be related directly to computable methods of determining whether or not meaning is preserved by some transformation on a representation of knowledge.
Any process or technique which constructs a well formed formula F_{output} from some other F_{input} is said to be valid if F_{input} entails F_{output}, otherwise invalid. Note that being an invalid process does not mean that the conclusion is false, and being valid does not guarantee truth. However, validity represents the best guarantee that any assertional language can offer: if given true inputs, it will never draw a false conclusion from them.
a procedure for translating expressions in L_{i} to expressions in L_{base}. This process will also consequently define the subset of L_{base} that is used by L_{i}.
a set of vocabulary items introduced by L_{i}
a set of axioms and/or axiom schemas (expressed in L_{base} or L_{base} schema) that define the semantics of the terms in (2).
Given a set of expressions G in L_{i}, we apply the procedure above to obtain a set of equivalent well formed formulae in L_{base}. We then conjoin these with the axioms associated with the vocabulary introduced by L_{i} (and any other language upon which L_{i} is layered). If there are associated axiom schemata, we appropriately instantiate these and conjoin them to these axioms. The resulting set, referred to as A(G), is the axiomatic equivalent of G.
As an illustrative example, we give in the following table a
sketch of the axiomatic equivalent for RDF graphs
using the RDF(S) and OWL vocabularies, in the form of a translation
from Ntriples. The translations given for the OWL vocabulary
reflect the 'OWLFull' version of the language; to accurately
reflect the more restricted OWLDL version would require the
L_{base} axioms to make finer distinctions such as between
the meanings of rdfs:Class
and owl:Class
.
The next table gives some of the axioms which wouild also be
required to support the meanings of the various namespaces. Therse
are largely simple trascriptions of conditions described in the RDF
Semantics documentation. Note, this should not be referred
to as an accurate or normative semantic description. It is
given here only to illustrate the axiomatic technique which
L_{base} is designed to support.
RDF expression E  Lbase expression TR[E]  add axiom 
"s"^^rdf:XMLLiteral where s is wellformed
XML 
the XML canonical form of s 
Lbase:XMLThing( TR[E]) 
"s"@tag^^rdf:XMLLiteral 
the XML canonical form of

Lbase:XMLThing( TR[E]) 
a plain literal "s"  's' with all occurrences of the symbols ',\,(,),<,> prefixed by \  
a plain literal "s"@tag  
a typed literal a^^d  the term
L2V( TR[a],TR[d]) 

a blank node  a variable (one distinct variable per blank node)  
any uriref a not in the rdf: ,
rdfs: or owl: namespaces 
a  
any uriref of the form rdf:_nnn 
rdfmember(nnn) 

rdfs:Resource 
T  
owl:Thing 
T  
owl:Nothing 
F  
owl:sameIndividualAs 
=  
a owl:differentIndividualFrom b 
not TR[a] =
TR[b] 

a owl:sameClassAs b . 
(forall (?u)(
TR[a](?u) iff TR[b](?u)
)) 

a owl:samePropertyAs b . 
(forall (?u ?v)(
TR[a](?u ?v) iff TR[b](?u
?v) )) 

a rdfs:SubClassOf b . 
(forall (?u)(
TR[a](?u) implies
TR[b](?u) ) 

a rdfs:subPropertyOf b . 
(forall (?u ?v)(
TR[a](?u ?v) implies
TR[b](?u ?v) ) 

a 
(forall (?u ?v)(
TR[a](?u ?v) iff TR[a](?v
?u)) 

a 


a 
(forall (?u ?v
?w)(( TR[a](?v ?u) and
TR[a](?w ?u)) implies ?v=?w) 

a 
(forall (?u ?v ?w) TR[a](?u ?v) and
TR[a](?v ?w)) implies
TR[a](?u ?w)) 

a 
(forall (?u
?v)( TR[a](?u ?v) iff
TR[b](?v ?u)) 

a owl:disjointWith b . 
not (exists (?u)( TR[a](?u)
and TR[b](?u) )) 

a owl:complementOf b . 
(forall (?u)( TR[a](?u) iff
not TR[b](?u) )) 

a owl:oneOf [[ b1 ... bn ]] 
(forall (?u)( TR[a](?u) iff
( a=TR[b1] or ... or
a=TR[bn]))) 

a owl:unionOf [[ b1 ... bn ]] 
(forall (?u)( TR[a](?u) iff
( TR[b1](?u) or ... or
TR[bn](?u) ))) 

a owl:intersectionOf [[ b1 ... bn ]] 
(forall (?u)( TR[a](?u) iff
( TR[b1](?u) and ... and
TR[bn](?u) ))) 

a owl:onProperty b .a owl:someValuesFrom c . 
(forall (?u)( TR[a](?u) iff
(exists (?v)( TR[b](?u ?v) and
TR[c](?v) )))) 

a owl:onProperty b .a owl:allValuesFrom c . 
(forall (?u)( TR[a](?u) iff
(forall (?v)( TR[b](?u ?v) implies
TR[c](?v) )))) 

a owl:onProperty b .a owl:hasValue c . 
(forall (?u) TR[a](?u)
iff TR[b](?u TR[c]) ) 

a owl:onProperty b .a owl:minCardinality n . 
(forall (?u)( TR[a](?u)
iff TR[b](?u ?x1) and ...and TR[b](?u
?xn) )) 

a owl:onProperty b .a owl:maxCardinality n . 
(forall (?u)( TR[a](?u)
iff TR[b](?u ?x1) and ...and
TR[b](?u ?xn+1) ))) 

a owl:onProperty b .a owl:Cardinality n . 


any other uriref a  a  
any other triple of the form a 
TR[b]( TR[a]) 
rdfs:Class( TR[b]) 
any other triple a b c . 
TR[b]( TR[a],TR[c]) 
rdfs:Property( TR[b]) 

The important point to note about the above diagram is that if the Li to L_{base} mapping and model theory for Li are done consistently, then the two 'routes' from G to a satisfying interpretation will be equivalent. This is because the L_{i} axioms included in the L_{base} equivalent of G should be sufficient to guarantee that any satisfying interpretation in the L_{base} model theory of the L_{base} equivalent of G will contain a substructure which is a satisfying interpretation of G according to the Li model theory, and vice versa.
The utility of this framework for combining assertions in
several different SWELs is illustrated by the following diagram,
which is an 'overlay' of two copies of the previous diagram.
Note that the G1+G2 equivalent in this case contains axioms for both languages, ensuring (if all is done properly) that any L_{base} interpretation will contain appropriate substructures for both sentences.
If the translations into L_{base} are appropriately defined at a sufficient level of detail, then even tighter semantic integration could be achieved, where expressions which 'mix' vocabulary from several SWELs could be given a coherent interpretation which satisfies the semantic conditions of both languages. This will be possible only when the SWELS have a particularly close relationship, however. In the particular case where one SWEL (the one used by G2) is layered on top of another (the one used by G1), the interpretations of G2 will be a subset of those of G1