Synonymy and Near-Synonymy
in Deep Lexical Semantics
Niloofar Montazeri and Jerry R. Hobbs
Information Sciences Institute
University of Southern California
Marina del Rey, CA
Deep Lexical Semantics:
Methodology
words
link with axioms
core theories
Construct core theories of abstract phenomena in various
domains
Express meanings of word senses as logical axioms in terms of
predicates in core theories
Core Theories and Lexical Periphery
Define (Characterize) words in terms supplied by the core
theories.
range(x,y,z) <-->
scale(s) &subscale(s1,s) & bottom(y,s1) & top(z,s1)
& in(u1,x) & at(u1,y) & in(u2,x) & at(u2,z)
& (u  x)( v  s1) at(u,v)
s
y
s1
v
z
x = {u1 . . . . . . . u . . . . . u2}
word: “range”
linking
axiom
core theory
Axiomatize core theories with richly explicated core predicates:
Core Theory of Scales: scale, <, subscale, top, bottom, at
Abstract Words in Context
By specializing “at” and the scale in various ways,
we can get a whole range of possible meanings
for “range”:
The scores on the test ranged from 33 to 96.
The timber wolf ranges from Mexico to the Arctic.
His behavior ranged from cheerful to sullen.
Deep Lexical Semantics
of Event-Related Words
(forall (x y z)
(iff (give x y z)
(exist (e1 e2 e3)
(and (cause x e1)(change’ e1 e2 e3)(have’ e2 x y)
(have’ e3 z y)))))
x gives y to z = x causes a change from x having y to z having y
Builds on old work by Gruber, Lakoff, Schank, Jackendoff, and
many others on lexical decomposition, but ....
“primative” predicates are explicated in core theories:
restricts possible interpretations of the predicates
enables reasoning within theory
logic, not syntax
Use in Textual Inference
T: Russia is blocking oil from entering Ukraine.
H: Oil cannot be delivered to Ukraine.
not’(n2,c2) & can’(c2,x2,d2) & deliver’(d2,x2,o2,u2)
Lexical
decomposition
axioms
cause’(d2,x2,c3) & changeTo’(c3,h2) & have’(h2,u2,o2)
possible’(p1,c4)
& cause’(c4,x3,e1)
in’(h2,o2,u2)
cause’(c1,x1,n1) & not’(n1,p1) & possible’(p1,e1)
block’(b1,x1,e1) & enter’(e1,o1,u1)
Defeasible
inferences
from
core theories
Core Theories: Change
change(e1,e2): state e1 changes into state e2
e1 and e2 involve a common entity;
change of state of something
Transitive if the something is the same
e1 and e2 are different unless there is an
intermediate state (cyclic change)
“move” is change of state of “at” relation
change(e1,e2) = changeFrom(e1) = changeTo(e2)
Theory of Causality:
Causal Complex
causal complex
s
e1
causal-complex(s,e)
e2
e3
e4
e
e1  s, ....
....
effect
When every event or state in s happens or holds,
then e happens or holds.
All eventualities in s are relevant to the effect.
A rigorous, nondefeasible notion, but can’t specify everything.
Theory of Causality: Cause
In a causal complex, some eventualities are
distinguished as causes.
presumable
power on
cause
finger in
socket
Causes are the focus of
planning, prediction,
explanation, interpreting
discourse
(but not diagnosis)
shock
What is presumable depends on
task, context, knowledge base, ....
“Cause” is a useful but defeasible notion.
Methodology
Having axiomatized these core theories, ....
Focus on most common 450 word senses involving
change of state and causality
Determine radial structure of set of WordNet senses of word,
and characterize by incremental differences in associated
axioms
Encode axioms for the most abstract or general senses or
“supersenses”
Evaluate on a textual entailment task
“Enter”
At each hop, we
specialize a predicate or
constrain an argument
enter-S1: x enters p
= changeTo(p(x))
enter-V2: enter a race
enter-V4: enter into calculations
enter-V9: enter into career
p = at/in
enter-S11: x enters y
= changeTo(in(x,y))
enter-V1: enter a room
enter-V6: enter from stage left
+ cause
enter-S2: x enters y in z
= cause(x,enter-S11(y,z))
Logically, and sometimes
chronologically
enter-V5: enter in ledger
enter-V8: enter picture into text
“Hit”
Supersenses give topological
structure.
Specific senses specialize
general predicates or
put constraints on arguments
hit-S1: x hits y
= changeTo(at(x,y))
We hit Detroit by noon.
The temperature hit -20.
+ sudden impact
hit-S11: x hits y
= changeTo’(e,in(x,y))
& sudden(e) & impact(x,y)
The car hit a tree.
+ cause
hit-S2: x hits z with y
= cause(x,hit-S11(y,z))
He hit the ball.
Synonymy and Near-Synonymy
Synonymy: The axiomatic lexical decompositions
are the same
Near-synonymy: The axiomatic lexical
decompositions differ only incrementally
(similar to word senses in radial structure)
“Receive” and “Get”
receive-S1: x receives y from z
= change(have(z,y), have(x,y)) -> changeTo(have(x,y))
= FrameNet sense 1
subsumes all of WordNet’s senses
where “have” is specialized to owning, having a property,
perceiving, hosting, etc.
get-S11: x gets y
= cause(x, changeTo(have(x,y)))
He always gets what he wants.
I’ll get the book at the library.
get-S12: x gets y
= changeTo(have(x,y))
He got the flu.
I got a call from Sue.
You’ll get your results tomorrow.
Synonyms or
near-synonyms
“Go”, “Hit”, and “Reach”
go-V1: x goes from e1 to e2
= change(e1,e2) & arg*(x,e1) & arg*(x,e2)
3rd
FrameNet
sense
go-FV3: specialize e1 and e2 to “at” relations
x goes from y to z
= change(at(x,y), at(x,z))
hit-S1: x hits z
= changeTo(at(x,z))
reach-S1: x reaches z
= changeTo(at(x,z))
x is an argument of ei
or a participant in ei
Not synonymous at
more general levels
of “go”
Not synonymous at
more specific levels
of “hit”
“Deliver”, “Give”, and “Provide”
deliver-S1: x delivers y from w to z
= cause(x, change(rel(y,w), rel(y,z)))
deliver-S11: specializes rel to have
stipulate that x = w
= cause(x, change(have(x,y), have(z,y)))
give-S0: cause(x, exist(y))
synonyms
give-S1: cause(x, change(have(x,y), have(z,y)))
provide-S1: x provides z with y
= cause(x, changeTo(possible(e))) & arg(y,e) & need(z,e)
provide for medical emergencies
provide-S11: possible(e) specializes to have(z,y)
= cause(x, changeTo(have(z,y))) & need(z,e)
near
synonyms
An Aside on “Need”
(Gordon& Hobbs)
In a core theory of cognition (based on beliefs and goals),
Define badFor(e,x) = e causes a goal of x’s not to happen
need(x,e) = cause(not(e), e1) & badFor(e1,x)
Overlapping Radial Structures
deliver-S1
give-S0
give-S1
deliver-S11
provide-S11
provide-S1
A Problem
Synonymy is a relation between word senses.
Carving the uses of words into word senses is highly arbitrary;
e.g., WordNet is very fine-grained; VerbNet less so.
word-1, sense-i
word-2, sense-j
Why not just stipulate that these are three different senses,
so that in the middle the senses are perfectly synonymous?
Context-Dependent Synonymy
give = cause to have
provide = cause to have + need
She gave food to the hungry man.
She provided food for the hungry man.
The sentences are equivalent even though “give” and “provide”
are only near synonyms.
Synonymous Specific Senses
So far the examples have been at an abstract level,
but intersection of radial structures can occur
at very specific levels too:
deliver-V1: deliver a talk
give-V12: give a talk
Small Perspective Differences:
Near Synonyms?
hold: x holds e
= cause(x, not(changeFrom(e)))
hold that pose
Specialize e to at: cause(x, not(changeFrom(at(y,z))))
hold the picture against the wall
block: x blocks e
= cause(x, not(changeTo(e)))
The senator blocked the judge’s appointment
Specialize e to at: cause(x, not(changeTo(at(y,z))))
He blocked my way
These can describe the same situation:
hold(x,e) = block(x,not(e))
“Capture” and “Seize”
x holds y = cause(x, not(changeFrom(at(y,z))))
x captures y = cause(x, changeTo(hold(x,y)))
“Seize”: Almost all senses of “seize” subsumed under
seize-S1: x seizes y
= cause’(e, x, changeTo(hold(x,y))) & forceful(e)
near
synonyms
Text Entailment Example:
Synonymy from Inference
H: The captors let the hostage go free.
let(x,e7) & go’(e17,y,e8) & free’(e8,y,c,e9)
not(e5) & cause’(e5,x,e6) & not’(e6,e7)
changeTo’(e7,e8)
not’(e8,e10) & cause(e10,c,e11) & not’(e11,e9) & move’(e9,y,z,w)
changeFrom’(e9,e12) & at’(e12,y,z)
Rexist(e0)
changeFrom’(e0,e1) & cause’(e1,x,e2) & not’(e2,e3) & changeFrom’(e3,e4) & at’(e4,y,z)
release(x,y,z)
T: A Filipino hostage in Iraq was released.
“Blunder” and “Lapse”
(Edmunds & Hirst)
blunder(e,x) = error(e,x) & cause(e1,e) & stupid’(e1,x)
lapse(e,x) = error(e,x) & cause(e1,e) & neglectful’(e1,x)
Need to capture meaning of “error” in theory of composite entities
as a mismatch between a composite entity and a pattern that
serves as a norm.
Need to capture meanings of “stupid” and “neglect” in theory
of cognition;
“stupid” in terms of ability to learn and reason
“neglect” in terms of model of attention
(Gordon & Hobbs)
Near Synonyms?
raise(x,y,z,w) = cause(x, change(at(y,z), at(y,w))) & above(w,z)
rise(y,z,w) = change(at(y,z), at(y,w)) & above(w,z)
Differ only by cause(x, ...)
raise(x,y,z,w) = cause(x, change(at(y,z), at(y,w))) & above(w,z)
lower(x,y,z,w) = cause(x, change(at(y,z), at(y,w))) & above(z,w)
Differ only in relation of w and z
To be near synonyms the words have to describe the same
situations.
Message
The meanings of word senses can be expressed as axioms
in terms of predicates from core theories of the
relevant phenomena.
The word senses of any word form a radial structure,
where adjacent nodes differ by incremental changes
in the axioms (specializations of predicates, constraints
on arguments).
Word senses of different words can have identical
axiomatic decompositions; this is synonymy.
Word senses of different words can have nearly identical
axiomatic decompositions -- is this near synonymy?
Is near synonymy a natural kind, about which we can make
reliable judgments?
More important than labeling word senses as near synonyms
is capturing the distinctions formally.