From: AAAI-84 Proceedings. Copyright ©1984, AAAI (www.aaai.org). All rights reserved.
Referential
Determinism
and Computational
Efficiency:
Posting Constraintsfrom
DeepStructure*
Gavan Duffy and John C. Mallet-y
Department
Massachusetts
of Political
Institute
Cambridge
Arpanet:
transformational
structures.
Instead
deep structures
conjunction
they
wrth
adopt
a reference
ccnstitutes
create
a surface-tnterpretlve
into
architecture
to include
We
Determinism
semantic
constraint
on
of
that our combination
theories
referential
of deep structures
non-determinism
immediate
in
constramt-posting,
We
find
at SRI
on
network.
In
syntactic
We
parsers
to NP resolution.
We show
the
and
the
that
by their
tl uses
in
may
the
hypothesis
structure,
rejected,
IS
and start
reasoner,
i!s
maximized
when
components
is
it
again.
does
backtrack,
erase
resources
not
It
is
and then,
if
non-deterministic.
It can hypothesize
some
become
Its
improves.
input
perform
can
As more
performance
its
necessarily
require
or
all
available
available
revision
of its
to such
resources
and
when
a
are
all other
deterministically.
and
view is consistent
sympathetic
speclficatlons.
to
Sentence
of Interpretation
example.
hypothesis
for
crucial
Relerent/al
this
a se!7tence
desires
analysis,
necessary
IS another
Prefer
linguists’
Marcus’
for
of course,
sentence
aspect.
that
Hypothesis
parsimonious
does
We
offer
[23]
grammar
not exhaust
understanding.
Defermimsm
analysis
Determinism
argue
constraint-posting
together
that
below
reference
they minimize
satisfy
referential
tl
this
the
provides
terms
view,
puts
signat
(;~ublic)
[27]
reference.
correspondence
recoverrng
III
circles
of
with
constraint
due
Berwick
because
non-determinism.
*
also
research
Massachl;setts
intelligence
Agency
was
done
of the
of
at
is provided
Department
the
Artificial
in
of Defense
part
by
under
finds
the
Office
fol
external
neither
IO.
as the
the
211.
[I].
Much
Instead,
Laboratory
of Naval
is
more
e.g.,
viftua!
spontaneous
if it can
and requires
complex.
It
depends
reasoning.
no
deliberative
need
as
for
Its
reference
In our
references
for
syntactic
inherent
beyond
to
thus
reference.
ambiguous
deliberation.
of deliberative
reference
and null
certain
possible
on the capacity
lmmcdiate
for
incorporate
arnong
first
incommensurate,
w?tt
may
to discriminate
ability
in
as
the
primanly
of
Grammar
to its
that
of
computationally
of
constraints.
approach
[6],
generative
complexity
the scope
of this
Grammar
derivations.
Al researchers
runs
briefly
certain
structure
exist
transition
from
criticisms.
rules,
view
modern
but
rather
guides
are the traditionat
only
rmplrcitly
their
both
cbservation
proposes
the
distinction
(SI)
analytic
and
trees
Berwick
approach
Theory”
was
a tractable
of TG in that light.
deep-structure
crucial
301.
not as a
annotation.
“Standard
Most
TG
as
in Al
[cf.
deep structure
in the
views
the traditional
Chomsky’s
controversial
intractability
a surtace-interpretive
annotatIon
to reconsider
as follows.
should
advocates
No longer
They
has remained
computational
mtractabte
Berwick
In surface
created.
(TG)
alleged
Al researchers
system
the
[5] was
to SI
open
that
to
logical
of
we
l
*Ken
Haase
“deliberative”
Since
the
[15]
class inclusion
only
bc known
Research
Projects
vittual-copy
Research
contract
that the class hierarchy
justifies
between
and
“spontaneous”
inference.
artificial
laboratory’s
Advdnced
Immediate
.*
no new structure,
is
of
a correspondence
Intelligence
Support
and
nor as the problem
[I:
reference
a hearer
Technology.
[26]
speakers
external
wherein
reference.
world
of
on
reference.
research
N00r)14-80-C-05rX.
meanings
concentrates
Institute
external
to an external
intended
internal
This
We do not discuss
(private)
structure.
are
explicit
from
inierences,
an inference
foundation
system
urges
internal
new
Al and Transformational
[4] argues
exptrcitty
Reference
distinguished
of terms
the
pragmatics
analyze
first
no
otf”
They
reference
paper.
The
Russell
relations
reasoning
contradictory.
discussion
below.
“read
creates
involved
references,
further
conceived
discussed
are
Immediate
just
referential
a bootstrapping
preliminary
immediate
Both
[2].* * *
complex
Deliberative
for
representations
theoretical
an
internal
Ireference:
ccmplexity.
We consider
Transformational
the non-determinism
deep-structure
limit
to Marcus’
reference.
We
161 constitutes
reterence.
spontaneous
reference
requiring
referents.
Hypothesis:
minimizes
on the
conducted
the range
Reference,
as a corollary
14,
however,
creating
utilize
deterministically,
Deliberative
constraints
locate
that
[8] or reflection
immediate
with
times
[3, 121.
constructions,
This
[13,
not,
do
of internal
computational
memory,
at
inheritance
deliberation
belief-revision.
We focus
Research
We
framework
constraints
representations
be computed
reasoning
syntax.
of NPs
dehberative
or
constraint-posting
reference
referential
copy
of non.monotonic
work.
two categories
medtated
distingllished
simpler.
eliminates
hypothesis.
Pragmatic
of the world.
public
resolution
reference
within
I Determinism
capable
model
using
of our
We distifiguish
analysis,
conclude
satisfy
referenttal
antecedent
reference
Hypothesis,
non-determinism.
reference.
or her
Marcus’
and constraint-posting
deep-structure
the
and his
of sentences
important
a foundational
Referential
that minimize
reference
extend
reference,
a sentence
private
on constraint-posting,
This
for theories
at MIT-MC
deep
approach.
based
rmmed/ate
explicit
a semantic
reference.
a
determinism
longer
non-determinism%
Hypothesis
of
no
for projection
referential
Determm~sm
subc!ass
they
JCMa
between
would
indIspensable
mlnlmlze
argumg
linguists
MA 02139
Gavan at MIT-MC,
Abstract
Most
Science
of Technology
inheritance
nothing
can be computed
to be inheritable
(not
quickly
actually
m the category
we place
of spontaneous
inference.
does not have exceptions
aside from
reference.
[24] and default
inherited),
relations
need
our version
of
We assume
and that the virtual inheritances
operations
can only
suggested
using
relations
while
scopes
development
of
could
structures
for
Shortly
thereafter,
“trace
theory”,
find
reference.
p%stmg,
we
from
SI
to be less
Together
with
the
deep-structures
parser*
principle
embodied
committing
to any
Backtracking
are
parse-tree
nodes
are
posted
Both
l l
possible
may
Using
implements
Before
The
sub-divide
191.
parser
transformational
* The
Mallery.
Gnoscere
networks.
Winston
analogical
reasoning
f7eldtl:s
trees compossd
This
some
parts
a sentence
!ransformational
of intelligent
and
semantic
the
tree
reference
creates
a
nodes
and headed
parser
which
feasibility
HAS-TENSE
HAS-ASPECT
by
system
of a real-time
network
that provides
PAST)
PERFECT)
The
represented
[31] showed
The mechanism
trees
hlallery
suited
in
bellcf
close
that
to
semantic
converts
with
netwol ks ate
representation
syntxtic
Gnoscele’s
collaboration
These
system
uses of a lelational
defap
reference
structure
system
Research
Duffy.
in
was
on
the
IS still preliminary.
algorithm
fan outtop-down according
would
to the branching
factor
Elmer
is
presented
reference
points
token
list
constrailit
for some
tree
crimes
in
marks
Figure
where
appiied
:oblect
srgnify
subject
and
object
verbs).
So
in Figure
reference
that
of that
takes
IS being
1, the
subject
In the reference
..I.
at the top.
parallel
algorithm
would
the bottom-most
perform
non-terminal
reference
nodes.
of
“fanning
the
constraint
into”
tree
the sentence
of ‘police’).
which
‘secret’.
The
participates
to ‘police’,
‘pokce
subject-relatiorr
as
A subject-relation
The
(oblecls
the
constraint
subject
They
omitted
indlvrdual-p
as opposed
of
IS
is
is
the
by the
and/or
designate
for
the
the
unergative
the
‘police’
to an ‘Elmer’.
constraint
subject
and thus
is followed
of the ‘want’ relation
the
State”
symbol
reference
keywords
are
wanted
of the
place,
xonsfrainfs
referenced.
is the reference
for an individual
police
appearance
following
keyword
relation
secret
symbol
In the reference.
a relation
and the object
are looklng
from
tor some
the totalitarian
reference
The
The
“The
against
every
a single
composltlon.
type to be referenced.
of constraints
committed
I\lote that
1.
points
of semantic
for the sentence
that were
of the deep structure.
A
Elmer
Figure 1: Constraint
tree for “The secret police wanted
crimes that were committed
by the totalitarian
sfate. ”
a constraint-posting
and a set of reference contraints.
It was implementgd by
is built out of a frame system and implements
multiple
.L.
bottom-up
T)
creates
nodes. was implemented by
the computational
HQ 1)
((TRUE))))
T)
((TRUE)
(PMSUBJECT-RELATION
TRANSFORMED-BY
PASSIVE-TRANSFORM
(PMSUBJECT-RELATION
HAS-TENSE
PAST)
(PMSUBJECT-RELATION
HAS-ASPECT
PERFECT)
(SUBJECT-RELATION
AGAINST
(REFERENCE
STATE
:CONSTRAINTS
((INDIVIDUAL-P)
(PNUMBER-OF-SUBJECT-RELATIONS
HQ 1)
(SUBJECT-RELATION
HQ TOTALITARIAN
((TRUE)
)))
:FORCE-NEW-P
NIL
:PARTICULAR-P
r)))))
:FORCE-NEW-P
NIL
:PARTICULAR-P
T))))
localizing
localization
specialist
suitable
[7].
:CONSTRAINTS
network.
of expert
of TG
((INDIVIDUAL-P)
(SUBJECT-RELATICN
HAS-QUANTITY
PLURAL)
(PMDBJECT-RELATION-TO-UNKNOWN
COMMI r
(RCFERENCE-UNKNOWN
*SOMETHING*
:CONSTRAINTS
((INDIVIDUAL-P)))
of the sentence
key,
environment
from the LF
The
semantic
two
existing
of the constraint
other
in deep
(LF).
and
traversal
of
tasks,
as a match
tree composed
is a de!erministic,
constramt
A parallel
tree
constraints,
one for each
lel&onal
Into
of subtrees
thO?lgh
into
phase,
match of the semantic
base is a semantic
mechanism
rmol~?rnented
only
depth-first
respective
reference
form
particular
to a network
differ
((INDIVIDUAL-P))
NIL
:PARTICULAR-P
((TRUE)
(PMSUBJECT-RELATION
(PMSUBJECT-RELATION
(SUBJECT-RELATION
FOR
(REFERENCE
CRIME
see”
avoidrng
depth-first
in
input
it
constrair?t
parse should go to Katz [20].
knowledge
tlees
even
for demonstratiny
reference
semanttc
its
their
In the
the constraint
structure
Credit
The
made
a subset
necessary)
support
any
its
their
unwinds,
The
explicit
logical
of
post
recursion
relationshlps
independent
within
to
VP node.
constitute
the constramts
ELMER
:CONSTRAINTS
:FORCE-NEW-P
:CONSTRAXNTS
[25],
and
are
tree is traversed
reference
a hierarchical
posting
Relatus
“wait
***
nodes.
from
(when
nodes.
deep structure
deep syntactic
l
created
phases
traversed
grammatical
or
this
(REFERENCE
POLICE
:CONSTRAINTS
((INDIVIDUAL-P)
(PNUMBER-OF-SUBJECT-RELATIONS
(SUBJECT-RELATION
HQ SECRET
:FORCE-NEW-P
NIL
:PARTICULAR-P
(REFERENCE
:OBJECT
thereby
decomposes
is
deep-structure
representation
canonicalized
Duffy
or
semantics
constructed
the successful
be new.
phase
:SUBJECT
explicit
than analysis.
decisions
they
When
to the top-level
constraints
“public”,
inference,
base,
by using
to
these
Because
the
is MUMBLE
is
recursively.
constituents
(REFERENCE
WANT
Below,
Posting
of action,
because
the constraint
to the deep-structure
makes
to
the
are
relations.
rather
us,
constraint-postmg
immedtate
tree attached
the canonical
For
network.
on,
supervises
its
have
knowledge
we gain
so
of
efficient
between
Relatus
course
parse-tree
tree,
Second,
In the semantic
l
on
constraint
referenced
*
the
generation
avoided
the
and
conserves
specrailst
each
a constraint
constraints
on constraint
situated
constraint-posting
syntax
First,
nodes.
notwork:
them
from
phases.
a
tree
is available.
Mapping
constramts
is
based
of constraint-posting
particular
We
and backtracking.
Using Constraint
use
in
it appears.
architecture
and
in sentence
when full information
than
for computattonnlly
of grammatical
for our
leaves
structure.
to dictate
the efficiencres
Reference
before
composes
are
surface
appeared
parsimonious
we Illustrate
telling
for logical
a reference
general
recursive
In the
parsimony
mechanism
co&traints
starts.
relations
left
7 he sentence
by
constraints,
began
relations
reference
A precedent
false
[l l]
and logical
recomputation
Immediate
posts
quantifier
Fiengo
by itself.
scope
relations
indispensable
for the analysis
IV
determining
grammatical
needless
Relatus
Below,
l l
level,
[18]
be abandoned.
transformational
which
the surface
Jackendoff
of grammatical
(pointers)
both the grammatical
they eliminate
Gnoscere.
which
of traces
deep structures
examine
in
Interpretation
be computed
We
level.
Interpretation
surface
Since
explicit
the
relations.
that deep structures
found
for
logical
by the
representation.
at the surface
structures
retaining
and other
determined
be determined
deep
means
an
l+iQ
constraint
to Its universal
we
(the class
that we want a ‘police’
(has-quality)
at1 ordinary
means
constraint.
relation
Ordinary
to
constraints
inverse
Only
are necessary.
A successful
of a subject-relation
relations
objects
have
referent
constraint
truth
value
is
constraints
may both have quantiflcational
must
satisfy
them.
object-refalion
an
(e.g.
constraints
The
true).
Relations
(e.g.,
decision-making
constraint.
syntactic
and
object
un/versa/-p).
told
(predicate
to post
its
individuals
A P
prefix
constraints.
These
Successful
order
selection
referents
successful
of
preference
distinguishes
the
PM,
also
use
but lhey
For
over
most
example,
1 does
by
scheme
to order
the successful
if the referent
preference
finds
aiding
constraints,
prefixed
with
semantic
possibility
space,
may
node’s
are
constraints
displaced
represented
instead
displacement
occurs
pmo@ect-relation
‘crime’.
raised
not itself
in
in
prepositional
is
explicrtly
nodes
exploit
their
posting
are
example,
in deep structure
appear
reference
Constraint:;
laughed”,
presented
of the
because
an unspecific
object
for
want
to
expltcltly.
constraints
positional
canonical
Restrictive
then
man
. . .>).
Smce
embedded
‘man’.
there
is
select
by the constraint
who
2, contain
The
was
the
the
no
to
the
supenor
for
The
by
the
The
object.
the
an explicit
is
are
embedded
referent
Quite
contrast,
specialist.
lf the NP scopes
constraints
and posts
is
a clause,
them as referential
it tells
decision-making
the c&se
restrrctions
by
to pass
on the noun.
posting
of
because
them in
NP
back
its
syntactic
Local
requiring
a referent
tree
node.
referent
returns
in
its own
the position
of
recomputation
“access”
be forced
third
are
repeatedly)
caches
the
forward.
clearly
the various
not
components
passed
would
in
would
approach.
(often
off
to backtrack
and reasoning
that
of
of a parse
alternative
approach
deep
be
less
It would
add
positional
and
parse-objects.
In
this
information
explicitly.
tree
without
repeatedly
deep
any
can
therefore
trees
simplify
need only
parse
localize
factor
that
without
full
need
only
to
retract
occur
in
constraint-posting
enough
tree nodes
and simplify
knowledge
to
constraints
or
remember
their
the algorithms
for
and reference.
of sentences
has
mmimlzes
three
representation
tree
will
fall
of the semantic
transformations
(e.g.,
for
nature
this
further
and
not
constituents
beneftcial
(belief
point.*
simplifies
representation
due
to syntactic
all
learning).
are
The
Since
syntactically
irregularities.
eliminates
on
the
The
effectively
it
the resulting
reference.
operations
parser
First,
network
revision).
Second,
the
representation
to canonical
effects.
of the semantic
backtracking
above illustrate
constraint
and
major
canonical
semantic
In the figures
reference
is taken
is no need to recompute
because
the (syntactically)
reference
parse
structures
reference
canonicalizatron
precludes
starts
There
is the critical
No action
the constituents
transformation
semantic
structure
information
case.
composition
before
an
A
deterministic.
ad hoc structures
The
the
would
SI
read
from
full
the canonical
The
103
simply
False
canonical
semantic
Once
require
interpretive
between
Canonical
thus
existing
node is found, a new
the returned
the deep-structure
reference.
and
using
reference
Reference
would
approach
reference
Use
constraints.
by the police
the
references.
guarantees
an
and in turn,
structures
premature
form
itself,
The
tree determines
in determining
is
top.
at any
the information.
immediate
constraint
tree,
the reference
than
structure
network
constraint
using
trees.
deliberative
store
itself
each
relationships
information
handle
T)
for
chosen,
efficient
the deep
by constituents
local
failure,
at the
references
and constraints.
approach
forcing
overhead
information.
exemplify
the
node
to constituents
finds
of immediate
constraint
order-of-evaluation
both
clauses
a new
for each node.
non-canonical
option
considerable
(created
canonical,
Relative
in
a semantic
to the superior
an St approach
of
Constraint
who was wanted
by the
node
sentence
If no suitable
references
SI
possibly,
and less
makes
“The man
begins.
reference
constraints.
of the constraint
an
in
node
representation
structures
the syntax,
“unpacking”
for
no
is
a
to the
associated
of reference
the
unpack
its
by the constraint
to
examples
tree
then
canonlcalizo
elegant
S.
((1RUE)
(PMSUBJECT-RELATION
TRANSFORMED-BY
PASSIVE-TRANSFORM)
(PMSUBJECT-RELATION
HAS-TENSE
PAST)
(PMSUEIJECT-RELATION
HAS-ASPECT
PERFECT))))
:FORCE-NEW-P
NIL
:PARTICULAR-P
T)
:CONSTRAINTS
((TRUE)
(PMSUBJECT-RkLATION
HAS-TENSE
PAST)
(PMSUBJECT-RELATION
HAS-ASPECT
PERFECT)))
Figure 2: Constraint
faug hed. ”
phase
be referenced.
Determinism
composition
tree
to the symbol
structure
data
Whichever
already
1) from the network.
((INDIVIDUAL-P))
NIL :PARTICULAR-P
constitute
corresponding
it is returned
Minimally,
The
(REFERENCE
LAUGH
:SUBJECT
(REFERENCE
MAN
:CONSTRAINTS
((INDIVIDUAL-P)
(PMDBJECT-RELATION
WANT
(REFERENCE
POLICE
:CONSTRAINTS
:FORCE-NEW-P
when
referenced
its constraints.
and order
intermediate
‘man’
and
semantic
object
V
police
on
constraints
the
‘want’
of
indexed
constraints
deep-structure
head
designated
reference.
are
objects
according
a
clauses,
includes
“unpack”
of
of an NP.
transformation
appropriate
tree in Figure
tree
classness
and object.
any referent
Only
constraint
non-terminal
reference
relative
transform’s
Because
riced
wanted
is
as
or
the reference
find
would
may successfully
(or created),
including
relative
a restrictive
VP
and object
on the subject
referential
behavior
satisfies
the position
plan
presence
modifiers
the parse
S,
to post
the
always
the
semantic
of the
which
is found
hierarchical
decisions,
as adjectival
I’1 he
for
passive
percolated
all
by
definiteness
constraints.
up the
of its
one IS created
CiauseS,
relative
structure
simplified
pre-determined.
in Figure
(<PMobject-relation
internal
is
embcddedness,
previously
with
symbol
mechanism
the
relation
of its
Each
the
of
uses
reference
grammatically
a “be”
its subject
tree is complete
constituents
any extant
referents
!ree
represented
example
the
by virtue
a unique,
deep-structure
easily
structure.
to the
and
the subject
Whenever
backtracking.
working
level in the trees
a
It iS
tree.
relation
for all adverbs,
other
subsequent
the
restrict
object
occurs
another,
An
‘commit’
to
a certain
encodes
Constraint
trans!orm
the
When
constraint
constraints.
constraint
Deep
of
Thus,
nodes.
node.
constraints
“to be”.
as constraints
we must
satisfies
Sentence
construction.
Parse-tree
The
Any
requiring
created
deep-structure
in the resulting
1 where
displacement
the
inter-constituent
of Figure
relation
to a higher
the
raised
Figure
phrases.
for corlstralnt-tree
constraints.
appear
the
on
nodes
onto
It to possess
Constraint
directly
lower
to-unknown
requlnng
connectivity,
from
are
node does
subject.
posted
be displaced
this
of
between
to classify
according
associated
network
created.
they specify.
in the top-level
and
bottom-up,
Constraints
and
its
symbol
for it.
They
it knows
universals
reference
one
this
interconstraints
of the verb
It then adds
In immediate
preferring
past>,
nominal)
Once the constraint
reference.
to have the feature
has-tense
or
implementation
the
constraints,
each [19, 221.
a referent
for the ‘want’ relation
not have <subject-relation
facilitates
e.g.,
constraints,
for
the referential
referent
ordinary
voting,
candldate
Preferred-mandatory
others.
from
unweighted
promising
for example:
the voting
require
need not satisfy
candidates
Pnumber-of-subject-re/at,ons,
tICI relation
constraints
also
constraints,
any
Third,
need
for
representation
compiles
out
syntax,
makmg
the semantic
representation
more efficient.
Constraint-posting
within
Consider
wanted
man”
man”.
The
in the sentence
embodded
S,
The
with
‘want’ relation
the
(e.g.,
would
be
resul!.
see
every
whether
versa.
The
a factor
The
it has
repeatedly
treated
been
of the size
steeper
as
would
size
is
units
increases
an SI
[7].
in
export
alternative
vice
reduced
force
of
syntax
are
emerge.
reference
constramts.
chores
our
would
do
At the
be forced
or be forced
Alternatively,
it
component.
may
Because
on the semantic
objection
a
mere
to semantics
claims
to the semantic
actlvitles,
From
approach
to deep-structure,
addltional
Canonicalization
by
manipulated.
be paid
semantic
component.
structures
enhances
referential
the
of
component
to it is concomitantly
reference,
and
The
network
A variant
remam
of
the
can rely
of SI which
be invented,
deep
deep
of
maximize
the
amount
of
in
the
necessary
of the referential
relations
the
and
composltion
turn,
minimizing
in
surface
of the
in
(belief-revision)
structure
may someday
no longer
consistency
of both
efficiency
thereby
grammatical
better.
enhances
constraints,
bzcktraskmg
representation
SI would
input
representation
elegance
in the semantic
perform
its
These
component.
operations
T)
of
Explicit
constramts.
canonicalized
thus
constramts
structure.
inherit
Inference
on that cnnonlcalization
supports
a canonical
but the parsimony
and
semantic
argument
for
tenable.
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