Category Archives: Propositions

That Strange Predicate/Relation IS

The predicate IS has two parameters.  Placing arguments in those parameters produces something like the following Relation:

IS (0)
THING PROPERTY
3 Prime
Car With Serial Number 1235813 Red
Rose With Barcode 3185321 Red
Grain Of Salt Mentioned By Hegel Cubical
Grain Of Salt Mentioned By Hegel White

This is a SINGLE relation, one may note, just as INVITES and TO_THE_LEFT_OF are. But while the relations INVITES and TO_THE_LEFT_OF are fairly easy to get one’s mind around, IS is a more difficult case. What is the relation between a property and the thing of which it is the property? Should we say that the property “inheres” in the thing? (Whatever “inheres” means.) Should we follow Plato and think of the relation between thing and property as analogous to the relation between reflection in the mirror and the thing or person reflected? So that the thing is a wholly relational entity wholly dependent upon something more real that exists independently, i.e., the property existing as a Platonic Form? Should we be more Aristotlean and think that, while yes, a given property (e.g. RED, e.g. PRIME) is one thing, not many, it is always already “contracted” (the ‘contracted’ business always makes me think of the old freeze-dried instance coffee commercials … the property gets “sucked” into the thing accompanied by the corresponding sound) ala John Duns Scotus into (but where does the ‘into’ come from? Does this mean ‘inhere’?) the thing so that it never exists independently of the thing? So that it has a “unity less than numerical?” (Source of the ‘unity less than numerical’ thing comes from some writing of Duns Scotus which I do not remember.) Should we think, along with William of Ockham, that it is nonsense to think of a single thing, e.g., the property RED, as existing in several places at the same time, so that we have to think of the red of the car and the red of the rose petal as in fact two different properties, even if they exactly match the same color sample held by the Interior Decorator? (So that ‘Red’ in the Relation above would always have to be marked by a number serving as an index?)

Or maybe the Relation IS is not a real Relation at all, but an artifact of a Word. Given the Word ‘is’, we think there is a corresponding Predicate generating Propositions which, when true, form a Relation. But in reality there is no such Relation. Perhaps?

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The Predicate Returns A Relation

We have seen that the predicate:

x is to the left of y

is mapped to the truth value TRUE when Charles is substituted for x and Genghis Khan is substituted for y.  The Relation TO_THE_LEFT_OF comprises all true propositions and only true propositions that get generated when values are substituted for x and y.  So the predicate is a function whose range is the truth value TRUE for every proposition that is included in the relation, and FALSE for every proposition that is not included in the relation.

I think, however, that we would get a slightly simpler account if we see the predicate as a function returning Relations comprising the single proposition TRUE, or the single proposition FALSE.  In the Relational Algebra, we would get a relation comprising the single tuple (and therefore proposition) TRUE if, after doing the Restriction that gives us:

Charles is to the left of Genghis Khan.

we then projected on the null set of attributes (“columns”).  We would then end up with Chris Date’s TABLE_DEE, that is, the Relation with cardinality 0 (o attributes, that is, 0 “columns”) and a single tuple.  TABLE_DEE is the Relation that corresponds to (I guess I should say ‘is identical with’) the weird classical logic proposition TRUE.  The predicate returns the proposition TRUE wrapped in the Relation TABLE_DEE when the Charles and Genghis Khan substitution is made.

Correspondingly, when John is substituted for x and Genghis Khan is subsituted for y, so that we get:

John is to the left of Genghis Khan.

the Restriction selects no tuple in the Relation TO_THE_LEFT_OF.  We then have a Derived Relation with a cardinality of 2 (i.e., the Relation has 2 “columns”) holding the null set of tuples.   If we then project on the null set of attributes, we end up with a Relation of cardinality 0 comprising 0 tuples.  Chris Date calls this Relation TABLE_DUM, and it holds the tuple, that is to say, the proposition FALSE.  The predicate returns the proposition FALSE wrapped in the Relation TABLE_DUM when the John and Genghis Khan substitution is made.

Thinking of the predicate as returning either TABLE_DEE or TABLE_DUM simplifies things a bit, because it means we never have to leave the Relational Algebra when modeling the predicate.  Everything gets explained in terms of just one set of operations, the operations of the Relational Algebra.

 

 

 


The Relational Algebra Gives Us Something (Or Somebody, Or At Least Someone)

Now onto trying to show how the Relational Algebra gives us ‘something’, ‘somebody’, ‘someone’, and so on.

When I talk about database relations in the following, I am, unless I state otherwise, talking about the abstract object, not those relations concretely realized in an RDBMS.

A brief explanation of the Relational Algebra:  Posit a world all of whose people are members of the set {John, Cliff, Charles, Genghis Khan, Leon Trotsky}.  Moreover, suppose that currently, the predicate:

 x is standing to the left of y

generates the Database Relation pictured below when all the members of this set are substituted for the parameters x and y:

TO_THE_LEFT_OF (0)
PERSON_ON_THE_LEFT PERSON_ON_THE_RIGHT
Charles Genghis Khan
Dan Leon Trotsky
Cliff Genghis Khan

(The above picture, by the way, is just that — a picture of the Relation.  It is not the Relation itself.)  As indicated by the number 0 in the name, this Relation is a base Relation, i.e., what we have before any operations are applied to it.

The Relational Algebraic operation RESTRICT is a function that takes the Relation pictured above as input and produces another Relation as output.  For example, the following RESTRICTion, expressed in Tutorial D:

TO_THE_LEFT_OF where PERSON_ON_THE_LEFT = ‘Charles’;  (Yes, I’ve suddenly gone from the flesh and blood Charles as member of a set to the name ‘Charles’; God only knows what confusions this sudden shift will introduce.)

generates the Relation pictured below:

TO_THE_LEFT_OF (1)
PERSON_ON_THE_LEFT PERSON_ON_THE_RIGHT
Charles Genghis Khan
Dan Leon Trotsky
Cliff Genghis Khan

The operation RESTRICT has given us a Relation comprising a single proposition expressed by the sentence ‘Charles is standing to the left of Genghis Khan.’  As indicated by the number 1, this is a Derived Relation, produced as output from a function that took as input the Base Relation.  The charcoal-grayed out portions of the picture are meant to convey that the derived relation is tied to the base relation in a way in which I will discuss later.

As with RESTRICT, the Relational Algebraic operation PROJECT takes the Base Relation as input and generates a Derived Relation as output.  The following RESTRICT and PROJECT operations, expressed in Tutorial D:

(TO_THE_LEFT_OF where PERSON_ON_THE_LEFT = ‘Charles’ ){PERSON_ON_THE_LEFT}

generates the Relation pictured below:

TO_THE_LEFT_OF (2)
PERSON_ON_THE_LEFT PERSON_ON_THE_RIGHT
Charles Genghis Khan
Dan Leon Trotsky
Cliff Genghis Khan

whose body is the set containing the tuple or proposition expressed by the sentence “Charles is to the left of somebody.”

But wait — all we see in this picture is the value Charles.  (Or, more precisely, the name ‘Charles’ appearing as a set of black pixels on a screen.)  Isn’t this a tuple in a one-place relation?  And if it is, wouldn’t it be a proposition belonging to one-place relation, a proposition such as “Charles laughs”, or “Charles runs”, or “Charles eats”?

Well, if it were such, it could be any proposition belonging to a one-place relation.  The only way to constrain which proposition this tuple is to just one proposition is to place it in its context, the source from which it is derived, i.e., the base relation TO_THE_LEFT_OF.  By performing the Projection, we are for the moment blacking-out the identity of Genghis Khan, the person to whom Charles is to the left, so that we can focus on the identity of Charles.  But we haven’t forgotten that we are working with the relation TO_THE_LEFT_OF, so we know that Charles is to the left of somebody.  We haven’t suddenly switched to the relations LAUGHS, or RUNS, or EATS.

To turn for the moment for relations concretely implemented in an RDBMS running in some stuff made out of the same substance as the red paint on the Golden Gate Bridge, complete chaos would ensue, the world would become a topsy-turvey place, objects would start falling up, if, say, a Projection on EMPLOYEE_NAME in the EMPLOYEE (select EMPLOYEE_NAME from EMPLOYEE) would result, not in the set of people employed by the company (more precisely, the set of propositions ‘John, employee of Widgets_R_US’, ‘Jesse, employee of Widgets_R_US’, and so on), but the set of people designated to live on Mars one moment, the set of ambassadors to Vietnam the next moment, and the set of of Pulitzer Prize winners the third moment.

So the meaning of a Projection on an attribute (“column”) of a relation is constrained by the relation from which it is standing out (“projecting”), so to speak.  The derived relation never ceases to, well, derive its meaning from the base relation.  It never ceases to be a derived relation.  Charles never ceases to be one member of a pair whose member on his right is being ignored or blacked-out for the moment.

(Compare this argument with C.J. Date’s argument in LOGIC AND DATABASES, pp. 387-391.)

Let’s trace then what happens, in this relational model, when we plug in Charles to replace x in the predicate:

Person x, to the left of somebody

The ‘somebody’ is not a parameter — no argument gets plugged into it — but it along with the x indicate that the base relation we are dealing with is TO_THE_LEFT_OF.  It tells us that one of the ‘central participants in the situation’ is some person to the right.  The relevant Relational Algebra Operations — the relevant RESTRICT and the relevant PROJECT — are then performed to generate the proposition:

Charles, to the left of somebody.

According to the Closed World Assumption, a Relation contains all and only those tuples — those propositions — those states of affairs — that obtain, and for which plugging in arguments to the parameters of the predicate defining the Relation results in a true sentence.  Therefore, each tuple in the Relation is paired with the truth value TRUE, and of course, within the Range comprising the two truth values, only the truth value TRUE.

So the set of tuples in a Relation and the set of Truth Values is a function.  So, finally — if I may end this string of ‘therefores’ and ‘so’s’ (“Feel free to come to the point when you finally decide what it is, I hear someone say”), when a single tuple is selected, as was done when the RESTRICT and PROJECT were performed on the Relation TO_THE_LEFT_OF, we can see this as the application of the function on that tuple, an application which returns TRUE.  So (this really is the final ‘so’ — I promise) plugging in the argument ‘Charles’ into the parameter x in the predicate:

x is to the left of somebody

triggers a RESTRICT and PROJECT on the Relation TO_THE_LEFT_OF, which in turn constitutes a selection of a single tuple in that relation, which in turn returns TRUE, which lets us regard the predicate as a function returning TRUE when ‘Charles’ is plugged into the parameter marked by x.

Just so, when the RESTRICT and PROJECT fail to select a tuple, as it does when we substitute ‘John’ for x (John is standing to the right of everyone else, including Genghis Khan), FALSE is returned.

Voila!  We now we have somebody (or, as the case may be, nobody).

It is clear that the predicate:

x is to the left of y

can be treated the same way.

Treating verbs aka predicates relationally this way — that is, as functions implemented by Relations and operations on Relations — has two advantages over simply seeing them as functions in the way described by Kroch and Santorini.  First, we get a semantics for ‘somebody’, ‘something’, etc.  Second, we have a way of conceptualizing in terms of operations of the Relational Algebra the select that occurs when, to use the verb laughs as our example, Luke is selected and the truth value TRUE is returned.  The notion of select is no longer a primitive.

 

Updated on 05/10/2012 to correct an obvious oversight.


The Predicate As A Truth Valued Function

So far we have been modeling sentences in which nothing is left unspecified.  Chris invites AndrewLukas laughs.  How could we model, however, sentences such as Chris invited someone, Someone invited Andrew, Someone invited someone, Joe ate something, Someone laughed … sentences in which at least one of the “central participants in a situation” is left unspecified?  We can model these sentences, I think, by applying the Relational Algebra to them — or, more precisely, to the propositions that underlie them.  In this post, I start laying the groundwork for showing how we can use the Relational Algebra to model sentences containing ‘someone’, ‘anyone’, and the like.

Let me begin by outlining the key premise behind Relational Database Theory: 

Predicates generate propositions which are either true or false.  A given Database Relation comprises all and only the true propositions generated by a given predicate.  (This is the Closed World Assumption.)  We can apply various operations of the Relational Algebra to the propositions contained in a Database Relation.

The key premise in Relational Database Theory talks about predicates.  What, then, is a predicate?

What the database theorist C.J. Date calls a predicate is what Kroch and Santorini call, in the primer on Chomskyan linguistics quoted from in the post below (The Verb Considered As A Function) a verb.  Date explains what a predicate is better than I can, so let him speak (LOGIC AND DATABASES THE ROOTS OF RELATIONAL THEORY, Trafford Publishing, Canada, 2007, p. 11):
 

A predicate in logic is a truth valued function.

In other words, a predicate is a function that, when invoked, returns a truth value.  Like all functions, it has a set of parameters; when it’s invoked, arguments are substituted for the parameters; substituting arguments for the parameters effectively converts the predicate into a proposition; and we say the arguments satisfy the predicate if and only if that proposition is true.  For example, the argument the sun satisfies the predicate “x is a star,” while the argument the moon does not. 

Let’s look at another example:

x is further away than y

This predicate involves two parameters, x and y.  Substituting arguments the sun for x and the moon for y yields a true proposition; substituting arguments the moon for x and the sun for y yields a false one. 
 

The key premise mentions Database Relations.  What, then, is a Database Relation?

The concept of a Database Relation is an elaboration on the concept of a Relation as defined in mathematics.  In mathematics, a Relation is defined as the subset of the Cartesian Product of two or more sets.  (What a Cartesian Product is will be obvious from the example.)  For example, in the sets {John, Charles, Cliff, Dan} and {Leon Trotsky, Genghis Khan}, the Cartesian Product is { (John; Leon Trotsky), (John; Genghis Khan), (Charles; Leon Trotsky), (Charles; Genghis Khan), (Cliff; Leon Trotsky), (Cliff; Genghis Khan), (Dan; Leon Trotsky), (Dan; Genghis Khan)}.  If, now, we pick out a subset of this Cartesian Product by seeing who happens to be standing to the left of whom at the moment, we get this Relation:  { (Charles; Genghis Khan), (Cliff; Genghis Khan), (Dan; Leon Trotsky)}. 

In other words, our Relation is what we get when we start with the predicate:

x is standing to the left of y

and plug in values for x from the set {John, Charles, Cliff, Dan} and values for y {Leon Trotsky, Genghis Khan}, throw away all the false propositions that result, and keep all of the true propositions.

Let me go out on a limb, then, and say that a proposition (remember, our key premise mentions propositions) is a tuple, that is to say, an ordered pair (for example, (Charles, Genghis Khan) ) in a Relation.  (Please, pretty please, don’t saw this limb off.) 

This means then that a proposition is a state of affairs ala R.M. Chisholm.  For example, the proposition Charles is standing to the left of Genghis Khan is the state of affairs comprising the flesh and blood Charles standing to the left of the flesh and blood Genghis Khan.  Propositions as states of affairs are the meaning of sentences… But I digress.

Back to Relations. 

A Database Relation, I have said, is an elaboration of a Mathematical Relation.  A Database Relation comprises a Heading consisting of ordered pairs of (Name Of Type; Type) and a Body consisting in a set of ordered pairs (Name Of Type, Value).  A type is a set, for example, the set of integers, the set of words in a given language, the set of people, the set of cities in the world, and so on.  A value of a type is a member of the set identical with that type.  I will leave name undefined. 

A Database Relation is an abstract object;  it is either an object really existing in some Platonic Heaven someplace or it is a fiction, depending upon which theory of abstract objects is the correct one.  Database Relations form the conceptual skeleton of databases concretely implemented by an RDBMS (Relational Database Management System) functioning inside a physical computer, but at least at the moment I am not talking about physical computers and the software they run.  I am talking about the abstract object, something that has the same status as the number 3 or the isoceles triangle. 

Why do I want to talk about Database Relations rather than Mathematical Relations?  It will be easier in the  posts that (hopefully) will follow to illustrate the Relational Algebra operations Projection and Restriction.  I know how to apply these operations to Database Relations; I am not sure how to apply them to Relations simpliciter.   Projection and Restriction are the Relational Algebra operations which, I claim, will give us a model for sentences such as Joe ate something. 

I’ve laid the groundwork for such a model; now let me go on to produce the model.