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Title: CAS LX 502


1
CAS LX 502
  • 8b. Formal semantics
  • A fragment of English

2
Infinite use, finite means
  • A fundamental property of language is its
    recursive naturewe can create unboundedly many
    new sentences, and understand what they mean.
  • Infinite use of finite means, one of the main
    reasons to suppose that our knowledge of language
    is systematic, that language is not a collection
    of habits and analogy, but must be described by a
    grammar.

3
Infinite use, finite means
  • In the domain of syntax, the task is primarily to
    describe/explain why some arrangements of words
    count as sentences of English, others dont, and
    more broadly, how this system relates to those
    underlying other languages, and how this system
    can arise.

4
Syntax
  • The generally accepted view of syntax breaks
    sentences down into hierarchical parts. There are
    nouns, there are verbs, there are units made of
    verbs and nouns. New sentences can be created by
    mixing and matching these components together.
  • S Pat AuxP will VP eat NP the sandwich
  • S The students AuxP have VP risen PP in
    protest

5
Semantics
  • Were not here to study syntax, were here to
    study semantics, but were going to delve a bit
    into both.
  • The syntactic system that defines what are good
    sentences of English provides hierarchical
    structures, but we know not only what sequences
    of words might be classified as English but we
    know what those sequences of words mean.
  • Just as there must be a grammar that defines what
    sequences of words are English, there must also
    be a grammar that tells us how the meanings of
    the parts contribute to the meaning of the whole.

6
F1
  • To that end, we are going to create a
    mini-grammar of English, a fragment. This
    grammar will provide both the syntactic structure
    of a small number of English sentences and the
    rules by which we can understand their meaning.
    By doing this, we can start to understand what is
    involved in the grammar of semantics more
    generally.

7
F1
  • Rewrite rules (the syntax)

S ? N VP N ? Pavarotti, Loren, Bond
S ? S conj S Vi ? is boring, is hungry, is cute
S ? neg S Vt ? likes
VP ? Vt N Conj ? and, or
VP ? Vi Neg ? it is not the case that
8
Using the syntax of F1
  • We start with S (we are building a sentence).

S
9
Using the syntax of F1
  • We start with S (we are building a sentence).
  • Several different rules can apply. We can either
    rewrite S as N VP, or as S conj S, or as neg S.
    Lets pick N VP.

S
VP
N
10
Using the syntax of F1
  • We start with S (we are building a sentence).
  • Several different rules can apply. We can either
    rewrite S as N VP, or as S conj S, or as neg S.
    Lets pick N VP.
  • Now, N can be rewritten as Pavarotti, Loren, or
    Bond.

S
VP
N
Bond
11
Using the syntax of F1
  • We start with S (we are building a sentence).
  • Several different rules can apply. We can either
    rewrite S as N VP, or as S conj S, or as neg S.
    Lets pick N VP.
  • Now, N can be rewritten as Pavarotti, Loren, or
    Bond.
  • And VP can be rewritten either as Vt N or Vi.

S
VP
N
Bond
Vi
12
Using the syntax of F1
  • We start with S (we are building a sentence).
  • Several different rules can apply. We can either
    rewrite S as N VP, or as S conj S, or as neg S.
    Lets pick N VP.
  • Now, N can be rewritten as Pavarotti, Loren, or
    Bond.
  • And VP can be rewritten either as Vt N or Vi.
  • And Vi can be rewritten as is boring, is hungry,
    or is cute.

S
VP
N
Bond
Vi
is hungry
13
Using the syntax of F1
  • With this little grammar, we can already create
    an unbounded number of sentences.
  • It is not the case that Bond is boring or Loren
    is hungry.

14
Using the syntax of F1
  • It is not the case that Bond is boring or Loren
    is hungry.

S
Neg
S
S
S
Conj
It is notthe case that
N
N
VP
VP
or
Bond
Vi
Loren
Vi
is boring
is hungry
15
Using the syntax of F1
  • It is not the case that Bond is boring or Loren
    is hungry.

S
S
S
Conj
N
S
VP
or
Neg
N
VP
Loren
Vi
It is notthe case that
Bond
Vi
is hungry
is boring
16
Compositionality
  • A fundamental assumption about how it is that we
    can know what novel sentences mean is that
    meaning is compositional.
  • The meaning of the whole is derived from the
    meaning of the parts and how the parts are
    arranged.
  • The syntax gives us the parts and how they are
    arranged, now we must approach the question of
    how the meaning is assigned to the parts and from
    there to the whole.

17
Enter M
  • Here, we turn to M, the evaluation function.
  • We already talked about the first steps
  • MltU,Fgt
  • PavarottiM F(Pavarotti) Pavarotti
  • LorenM F(Loren) Loren
  • BondM F(Bond) Bond
  • is boringM F(is boring) Loren, Pavarotti
  • is hungryM F(is hungry) Bond, Pavarotti
  • is cuteM F(is cute) Loren, Bond

18
M
S
  • We can write the denotation of the terminal nodes
    using those rules.

VP
N
Bond
Vi
BondM F(Bond) Bond
is hungry
is hungryM F(is hungry) Bond, Pavarotti
19
M
S
  • We can write the denotation of the terminal nodes
    using those rules.
  • And, on the principle of compositionality, we can
    assume the that nodes above share the same
    denotation (where there is no combination
    involved)

VP
N
Bond
Vi
BondM F(Bond) Bond
is hungry
is hungryM F(is hungry) Bond, Pavarotti
20
M
S
  • Now, to determine the meaning of the S as a
    whole, we want to combine the denotation of N and
    VP such that the S is true just in case (here),
    Bond is hungry.
  • That is, true just in case NM is in the set
    VPM.

VP
N
Bond
Vi
BondM F(Bond) Bond
is hungry
is hungryM F(is hungry) Bond, Pavarotti
21
M
S
  • We can define a semantic rule for interpretation
    that says just that
  • S N VPM true iffNM ? VPM,otherwise
    false.

VP
N
Bond
Vi
BondM F(Bond) Bond
is hungry
is hungryM F(is hungry) Bond, Pavarotti
22
M
S
  • Thus, we end up with an interpretation of this
    sentence that goes like this
  • SM true iffF(Bond) ? F(is hungry), otherwise
    false.
  • Given this particular model, that boils down to
  • SM true iff Bond ? Bond, Pavarotti,
    otherwise false.
  • (True in this situation)

VP
N
Bond
Vi
BondM F(Bond) Bond
is hungry
is hungryM F(is hungry) Bond, Pavarotti
23
A semantic rule for every structural rule
  • Our goal is to design a semantics for F1 that can
    provide an interpretation (truth conditions) for
    any structure that the syntax can provide.
  • So, we also need rules for structures like S conj
    S, neg S, Vt N.

24
Neg S
  • As for Neg S, we want it to be false whenever S
    is true, and true whenever S is false.
  • Neg SM false if SM true, true if SM
    false.
  • However, this is not quite enoughwe want to have
    an interpretation for every node in the tree.
    This gives us an interpretation of S Neg S, but
    what is the interpretation of Neg?

25
Neg
  • What Neg does is takes the truth value of the S
    it is next to and reverses it.
  • It is a functionit takes the truth value of the
    S it is next to as an argument, and returns a
    truth value (the opposite one).
  • it is not the case thatM true ?
    false false ? true

26
Neg S
  • S Neg It is not the case that S Pavarotti is
    boring.
  • NegM It is not the case thatM true ?
    false false ? true
  • SM true iff NM ? VPM, otherwise false
    true iff PavarottiM ? ViM, otherwise false
    true iff PavarottiM ? is boringM, otherwise
    false F(Pavarotti) ? F(is boring), otherwise
    false

27
Neg S
  • S Neg It is not the case that S Pavarotti is
    boring.
  • And, so S Neg SM NegM ( SM ).
  • Resulting in
  • SM false if F(Pavarotti) ? F(is
    boring),otherwise true.

28
And
  • For dealing with and and or, we also want to
    define a function. We want S1 and S2 to be true
    when S1 is true and S2 is true, and false under
    any other circumstance.
  • S S1 Conj S2M ConjM ( lt S1M, S2M gt )
  • andM lt true, true gt ? true lt true, false
    gt ? false lt false, true gt ? false lt false,
    false gt ? false

29
Or
  • For dealing with and and or, we also want to
    define a function. We want S1 or S2 to be false
    when S1 is false and S2 is false , and true under
    any other circumstance.
  • S S1 Conj S2M ConjM ( lt S1M, S2M gt )
  • orM lt true, true gt ? true lt true, false
    gt ? true lt false, true gt ? true lt false,
    false gt ? false

30
Revisiting verbs
  • Earlier, we defined a meaning for is boring by
    explicitly listing the set of boring individuals.
    This relies on a specific model/situation. We
    want to be more general than that, so that our
    interpretation rules work in any model.
  • is boringM x x is boring in M
  • is boringM x ? U x ? F(is boring)

31
Generalizing
  • We also do not yet have a general statement of
    how to evaluate S N VPM.
  • VP Vi is boringM x x is boring in M
  • S N VPM true iff NM ? VPM, otherwise
    false

32
Transitive verbs
  • The one piece of the model that we have not
    addressed yet are transitive verbs, like likes.
  • S ? N VP
  • VP ? Vt N
  • Vt ? likes
  • We want to be able to evaluate S N VPM the same
    way whether VP is built from a transitive verb or
    an intransitive verb. That is, we want VPM to
    be a predicate, a set of individuals.

33
Transitive verbs
  • Essentially, we want likes BondM to be a set of
    those individuals that like Bond in M.
  • However, we need a definition for likesM (we
    already have one for BondM). It should be
    something that creates a set of individuals that
    depends on the individual next to it in the
    structure. A function again.

34
Transitive verbs
  • Like and, likes relates two things, although
    likes relates two individuals, and and relates
    two sentences.
  • So, we build a two-place predicate, in the same
    way
  • likesM ltx,ygt x likes y in M
  • For example, if P likes L, L likes B and thats
    all the liking in this situation, then likesM
    ltP,Lgt, ltL,Bgt

35
Transitive verbs
  • And then, we define a rule that will interpret
    the VP in a sentence with a transitive verb
  • VP Vt NM x lt x, NM gt ? VtM
  • So if NM Bond, then VP Vt NM is the set
    containing those individuals who like Bond in M.

36
S ? N VP S N VPM true iff NM ? VPM, otherwise false
S ? S Conj S S S1 Conj S2M ConjM ( lt S1M, S2M gt )
S ? Neg S S Neg SM NegM ( SM ).
VP ? Vt N VP Vt NM x lt x, NM gt ? VtM
VP ? Vi
N ? Pavarotti, PavarottiM F(Pavarotti)
Vi ? is boring, is boringM x x is boring in M
Vt ? likes likesM ltx,ygt x likes y in M
Conj ? and, andM ltlttrue,truegt,truegt, lttrue,falsegt,falsegt,
Neg ? it is not the case that iintctM lttrue,falsegt, ltfalse,truegt
37
What we have
  • We have created a little fragment describing a
    (very small) subset of English, generating
    structural descriptions of syntactically valid
    sentences and providing the means to determine
    the truth conditions of these sentences.
  • We did this by formulating a set of syntactic
    rewrite rules, each accompanied by a semantic
    rule of interpretation, such that every syntactic
    step can be interpreted compositionally.

38
One step more general
  • Looking over the rules that we have, we can
    actually go a step further in generalizing our
    semantic rules (helpful as we expand our
    fragments coverage).
  • There are basically two kinds of rules we have
    Those that combine meanings of adjacent (sister)
    nodes in the syntactic structure, and those that
    define intrinsic (non-compositional) meanings.

39
Semantic type
  • The entire semantics that we are creating here
    depends on two types of things, individuals and
    truth values.
  • We can label individuals as being of type e
    (traditional, think entity), and truth values
    as being of type t.
  • In these terms, names like Bond are of type ltegt,
    and sentences like Bond is hungry are of type lttgt.

40
Characteristic functions
  • For predicates like is hungry, we have considered
    these to be sets of individuals (e.g., those that
    are hungry in the model).
  • We can look at those same individuals in a
    slightly different way, using the characteristic
    function of the set.
  • A characteristic function is a function that,
    given an argument, will return true iff the
    argument was a member of the set, and false
    otherwise. The same information content as the
    set.

41
Predicates as functions
  • So, without losing information, we can view
    predicates from the perspective of their
    characteristic functions and define is hungry to
    instead be a function that, given an individual,
    will return true if the individual is hungry in
    the model.
  • is hungryM x ? true if x is hungry in M x
    ? false otherwise

42
Semantic type
  • Predicates like is hungry can then be said to
    have semantic type lte,tgt. That is, a function
    from individuals to truth values.
  • Similarly, it is not the case that can be taken
    to be of type ltt,tgt, a function from truth values
    to truth values.

43
Transitive verbs
  • For transitive verbs, what we want is a relation
    between two individuals, resulting in a truth
    value. The way we have it set up now, a verb like
    likes will combine with the object to form a
    simpler predicate like likes Bond, at which point
    it acts just like is boring.
  • So, here, we want likes to take an argument of
    type ltegt and return a predicate of type lte,tgt.
    So, we define it as a function of type lte,lte,tgtgt.

44
Transitive verbs
  • That is, we can define likesM as something like
    this
  • likesM x ? f where f is a function from
    individuals to truth values and f(y) true iff y
    likes x in M, otherwise false.
  • That is, likesM is a function from individuals
    to functions (from individuals to truth values)
    semantic type lte,lte,tgtgt.

45
Why were doing this
  • Once we have defined things in terms of semantic
    type, and in terms of functions and arguments, we
    can collapse a number of our semantic
    interpretation rules into more general rules.
  • Functional applicationa bM aM (bM ) or
    bM (aM), whichever is defined.
  • Pass upb aM aM

46
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