Psy1302 Psychology of Language Lecture 10 Ambiguity Resolution Sentence Processing I.
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Psy1302 Psy1302 Psychology of LanguagePsychology of Language
Lecture 10Lecture 10
Ambiguity ResolutionAmbiguity Resolution
Sentence Processing ISentence Processing I
agendaagenda
Connecting word recognition with Connecting word recognition with sentence processing via ambiguity sentence processing via ambiguity resolution.resolution.
Lexical AmbiguityLexical Ambiguity Syntactic AmbiguitySyntactic Ambiguity
– & MORE MODELS!!!& MORE MODELS!!! Garden-Path ModelGarden-Path Model Constraint-Satisfaction ModelConstraint-Satisfaction Model
– & CLEVER but difficult to explain & CLEVER but difficult to explain experiments!experiments!
(so ask questions if you are lost!!!)(so ask questions if you are lost!!!)
AmbiguityAmbiguityTime flies like an arrowTime flies like an arrow
– Time proceeds as quickly as an arrow Time proceeds as quickly as an arrow proceeds.proceeds.
– Measure the speed of flies in the same way Measure the speed of flies in the same way that you measure the speed of an arrow.that you measure the speed of an arrow.
– Measure the speed of flies in the same way Measure the speed of flies in the same way that an arrow measures the speed of flies.that an arrow measures the speed of flies.
– Measure the speed of flies that resemble Measure the speed of flies that resemble an arrow.an arrow.
– Flies of a particular kind, time flies, are Flies of a particular kind, time flies, are fond of an arrow.fond of an arrow.
Qs about Online Ambiguity Qs about Online Ambiguity ResolutionResolution What alternatives are available at What alternatives are available at
different time points?different time points? What degree of commitment is What degree of commitment is
made to one or more made to one or more alternatives?alternatives?
What information is used to guide What information is used to guide these commitments?these commitments?
Cross-Modal Priming Exp. Cross-Modal Priming Exp. 11(Swinney et al. 1978; Onifer & Swinney, (Swinney et al. 1978; Onifer & Swinney, 1981)1981)Rumour had it that for many years, the government Rumour had it that for many years, the government building had been plagued with problems. The man building had been plagued with problems. The man was not surprised when he found several (spiders, was not surprised when he found several (spiders, roaches, and other) bugs in the corner of his room.roaches, and other) bugs in the corner of his room.
ANT
SPY
SEW
ANT
SPY
SEW
{
0
10
20
30
40
50
60
70
80
immediate 3 syll
delay
Am
ou
nt
of
Pri
min
g(u
nre
late
d w
ord
RT m
inu
s
rela
ted
word
RT)
“ant”
“spy”
Cross-Modal Priming Exp. Cross-Modal Priming Exp. 11(Swinney et al. 1978; Onifer & Swinney, (Swinney et al. 1978; Onifer & Swinney, 1981)1981)
Cross-Modal Priming Exp. Cross-Modal Priming Exp. 11(Swinney et al. 1978; Onifer & Swinney, (Swinney et al. 1978; Onifer & Swinney, 1981)1981)Rumour had it that for many years, the government Rumour had it that for many years, the government building had been plagued with problems. The man was building had been plagued with problems. The man was not surprised when he found several (spiders, roaches, not surprised when he found several (spiders, roaches, and other) bugs (insects) in the corner of his room.and other) bugs (insects) in the corner of his room.
ANT
SPY
SEW
ANT
SPY
SEW
{
RiddleRiddle What has wheels and flies, but is not What has wheels and flies, but is not
an airplane?an airplane?
What [has wheels] and [flies], but is What [has wheels] and [flies], but is not an airplane?not an airplane?
What has [wheels and flies], but is not What has [wheels and flies], but is not an airplane?an airplane?
V
N
Cross-Modal Priming Exp. Cross-Modal Priming Exp. 22(Tanenhaus, Leiman, & Seidenberg, 1979; (Tanenhaus, Leiman, & Seidenberg, 1979; Seidenberg, Tanenhaus, Leiman, & Seidenberg, Tanenhaus, Leiman, & Bienkowski, 1982)Bienkowski, 1982) Noun reading: I bought a Noun reading: I bought a watchwatch..
Verb reading: I will Verb reading: I will watchwatch..
0 200 600
0 200 600
CLOCK
CLOCK
Cross-Modal Priming Exp. 2Cross-Modal Priming Exp. 2(Tanenhaus, Leiman, & Seidenberg, 1979; (Tanenhaus, Leiman, & Seidenberg, 1979; Seidenberg, Tanenhaus, Leiman, & Seidenberg, Tanenhaus, Leiman, & Bienkowski, 1982)Bienkowski, 1982)
Noun reading: I bought a Noun reading: I bought a watchwatch..
Verb reading: I will Verb reading: I will watchwatch..
0 200 600
0 200 600
clock
clock
clock
clock
clock
clock
Effects of Frequency in Effects of Frequency in Ambiguity ResolutionsAmbiguity Resolutions
pitcher port
Equibias Ambiguous Word
Non-Equibias Ambiguous Word
Duffy, Morris, & Rayner Duffy, Morris, & Rayner (1988)(1988)
Varied frequency of homonymsVaried frequency of homonyms Varied whether supportive Varied whether supportive
context came before word or after context came before word or after word.word.
low-level low-level infrared light infrared light eye eye
reflections reflections from cornea from cornea and lens and lens indicate indicate position of position of eye fixation.eye fixation.
Older Eye-trackerOlder Eye-tracker
Head movements messes up calibration Bite bar or head rest is needed
*Control words in Parentheses
*For Non-Equibiased, Context supports non-dominant reading.
Duffy, Morris, & Rayner Duffy, Morris, & Rayner (1988)(1988)
Supportive Context
No Supportive Context
Supportive Context
No Supportive Context
pitcher
port
Equibias Ambiguous Word
Non-Equibias Ambiguous Word
whiskeyNon-Ambiguous Control
soupNon-Ambiguous Control
No Supportive ContextNo Supportive Context
-- Thickness of the line indicates amount of activation.
pitcher
port
Equibias Ambiguous Word
Non-Equibias Ambiguous Word
whiskeyNon-Ambiguous Control
soupNon-Ambiguous Control
Adding Supportive Adding Supportive ContextContext
-- Thickness of line indicates amount of activation.
+ supportive context
+ supportive context
pitcher + supportive context
port
Equibias
Non-Equibias
+ supportive context
Supportive Context No Supportive Context
= High reaction time
Equibiased: Equibiased: – Processing time lower when provided with prior disambiguating Processing time lower when provided with prior disambiguating
contextual support. (Reason: because accessing both contextual support. (Reason: because accessing both meanings)meanings)
Non-equibiased:Non-equibiased:– Processing time high when provided with prior disambiguating Processing time high when provided with prior disambiguating
contextual support supporting the less frequent meaning. contextual support supporting the less frequent meaning. (Reason: made the less frequent more “equal” to the other (Reason: made the less frequent more “equal” to the other meaning)meaning)
– Processing time low when not provided disambiguating Processing time low when not provided disambiguating contextual support for the less frequent meaning. (Reason: not contextual support for the less frequent meaning. (Reason: not considering the less frequent meaning. In fact, time spent later considering the less frequent meaning. In fact, time spent later in disambiguating region is higher due to a need to reanalyze).in disambiguating region is higher due to a need to reanalyze).
Supportive Context No Supportive Context
Lexical AmbiguityLexical Ambiguity
Current conclusionsCurrent conclusions Parallel, rather than serial Parallel, rather than serial
activation activation Relative strength of activation Relative strength of activation
depends on: depends on: – Degree of contextual constraint Degree of contextual constraint
available available – Frequency of use of each meaning Frequency of use of each meaning
SyntaxSyntax
Another level up!Another level up! ParsingParsing:: figuring how the words figuring how the words
in a phrase or sentence combine, in a phrase or sentence combine, using the rules in a grammar.using the rules in a grammar.
ParserParser
Is the woman insured?Is the woman insured?
Woman drives off with what she Woman drives off with what she thought was her date’s car (but wasn’t) thought was her date’s car (but wasn’t) and then totaled it. Can she get money and then totaled it. Can she get money from her insurance company:from her insurance company:
Contract says:Contract says:– Such insurance as is provided by this policy Such insurance as is provided by this policy
applies to the use of a non-owned vehicle applies to the use of a non-owned vehicle by the named insured and any person by the named insured and any person responsible for use by the named insured responsible for use by the named insured provided such use is with the permission of provided such use is with the permission of the owner.the owner.
Does he deserve jail Does he deserve jail time?time?
Drug dealer tried to swindle an (unbeknownst to him) Drug dealer tried to swindle an (unbeknownst to him) undercover cop by selling a bag of powder that had undercover cop by selling a bag of powder that had only a minuscule trace of methamhetamine. The only a minuscule trace of methamhetamine. The quantity was not harmful.quantity was not harmful.
Law saysLaw says– Every person who sells any controlled substance Every person who sells any controlled substance
which is specified in subdivision (d) shall be which is specified in subdivision (d) shall be punished.punished.
– (d) Any material, compound, mixture, or (d) Any material, compound, mixture, or preparation which contains any quantity of the preparation which contains any quantity of the following substance having a potential abuse following substance having a potential abuse associated with a stimulant effect on the central associated with a stimulant effect on the central nervous system: Amphetamine, nervous system: Amphetamine, Methamphetamine…Methamphetamine…
The bully hit the girl The bully hit the girl with thewith the......
...stick....stick.
...wart....wart. (*garden-pathed)(*garden-pathed)
The woman felt The woman felt the furthe fur......
...and then left....and then left. ...was very expensive. ...was very expensive. (*garden-pathed)(*garden-pathed)
Local Ambiguities Local Ambiguities (Being led down the “garden-(Being led down the “garden-path”)path”)
Local AmbiguitiesLocal Ambiguities
The bully hit the girl with the wart and then…The bully hit the girl with the wart and then…
The bully hit the girl with the stick and then…The bully hit the girl with the stick and then…
Ambiguous SentencesAmbiguous Sentences
time
yesterday today
Last night, the car crashed.
time
yesterday today
The car crashed.
The reporter said the car crashed last night.
Homework sentence
Ambiguous SentencesAmbiguous Sentences
time
…car...
time
…car....
The reporter said the car crashed last night.
S
NP VP
S AdvP
NP
V
VP
The reportersaid
last night
the carcrashed
V
The reporter
NP VP
S
NP
V
VPsaid
the carcrashed
S
V AdvP
last night
Ambiguous SentencesAmbiguous Sentences
Jamie saw the man with the telescope.
S
NP VP
PN NP PPV
Det N P NPJamie saw
the manwith
the telescope
S
NP VP
PN NP
PPV
Det N P NP
Jamie saw
the manwiththe telescope
NP
Traditional ViewsTraditional Views(contrasting lexical and syntactic (contrasting lexical and syntactic ambiguity)ambiguity)
Table from MacDonald, Pearlmutter, & Seidenberg Paper
Garden-Path ModelGarden-Path Model(Frazier & Fodor, 1978)(Frazier & Fodor, 1978)
Serial:Serial: the processor initially the processor initially identifies only one analysisidentifies only one analysis– selected based on structural simplicityselected based on structural simplicity
Modular:Modular: Initial structure built on Initial structure built on the basis of syntactic category the basis of syntactic category labels.labels.– revision process incorporates other revision process incorporates other
information.information.
Garden Path ModelGarden Path ModelSelecting the initial analysisSelecting the initial analysis
When word is identified, its syntactic When word is identified, its syntactic category is retrievedcategory is retrieved
Parser identifies which rules of the grammar Parser identifies which rules of the grammar contain that categorycontain that category
Analysis selected on the basis of structural Analysis selected on the basis of structural simplicitysimplicity– Late ClosureLate Closure– Minimal AttachmentMinimal Attachment
Garden Path ModelGarden Path ModelHeuristics for SimplicityHeuristics for Simplicity
Late ClosureLate Closure– When possible, attach incoming lexical When possible, attach incoming lexical
items into the clause or phrase currently items into the clause or phrase currently being processed (i.e., the lowest possible being processed (i.e., the lowest possible nonterminal node dominating the last item nonterminal node dominating the last item analyzed).analyzed).
Minimal AttachmentMinimal Attachment– Attach incoming lexical items into the Attach incoming lexical items into the
phrase-marker being constructed with the phrase-marker being constructed with the fewest nodes consistent with well-fewest nodes consistent with well-formedness rules of language.formedness rules of language.
Late ClosureLate Closure
time
yesterday today
..car…
time
yesterday today
..car…
S
NP VP
S AdvPNP
V
VP
The reportersaid
last night
the carcrashed
V
The reporter
NP VP
S
NP
V
VP
said
the carcrashed
S
V AdvP
last night
Late ClosureLate Closure
The reporter said the car crashed last night
S
VP
Vsaid
The reporter
NP
NP
the car
S
VP
crashedV
AdvP
last night
1 or 2?1
2
Late ClosureLate Closure Choice #1Choice #1 Choice #2Choice #2
…car...
time
Last night…
S
NP VP
S AdvP
NP
V
VP
The reportersaid
last night
the carcrashed
V
The reporter
NP VP
S
NP
V
VPsaid
the carcrashed
S
V AdvP
last night
Minimal AttachmentMinimal AttachmentS
NP VP
PN NP PPV
Det N P NPJamie saw
the manwith
the telescopeS
NP VP
PN NP
PPV
Det N P NP
Jamie saw
the man withthe telescope
NP
Minimal AttachmentMinimal Attachment
NP
PNJamie
S
VP
Vsaw
Jamie saw the man with
PP
Pwith
1 or 2?
NP
theDet
man
N
1
2
Minimal AttachmentMinimal Attachment Choice #1Choice #1
PP
Pwith
NP
PNJamie
S
VP
Vsaw
NP
theDet
man
NPP
Pwith
NP
PNJamie
S
VP
Vsaw
NP
theDet NP
Choice #2Choice #2
NP Det + NNP NP + PP
manN
1 extra node
Garden Path ModelGarden Path ModelHeuristics for SimplicityHeuristics for Simplicity
Late ClosureLate Closure– When possible, attach incoming lexical When possible, attach incoming lexical
items into the clause or phrase currently items into the clause or phrase currently being processed (i.e., the lowest possible being processed (i.e., the lowest possible nonterminal node dominating the last item nonterminal node dominating the last item analyzed).analyzed).
Minimal AttachmentMinimal Attachment– Attach incoming lexical items into the Attach incoming lexical items into the
phrase-marker being constructed with the phrase-marker being constructed with the fewest nodes consistent with well-fewest nodes consistent with well-formedness rules of language.formedness rules of language.
Ambiguities: Ambiguities: Late Closure and Minimal Late Closure and Minimal AttachmentAttachment NP/VP Attachment Ambiguity:NP/VP Attachment Ambiguity:
– The cop [saw [the burglar] [with the binoculars]]The cop [saw [the burglar] [with the binoculars]]
– The cop saw [the burglar [with the gun]]The cop saw [the burglar [with the gun]]
In-Class Exercise (see also homework)
Ambiguities: Ambiguities: Late Closure and Minimal Late Closure and Minimal AttachmentAttachment
NP/S Complement Attachment Ambiguity:NP/S Complement Attachment Ambiguity:
– The athlete [realized [his goal]] last weekThe athlete [realized [his goal]] last week
– The athlete realized [[his shoes] were across the room]The athlete realized [[his shoes] were across the room]
In-Class Exercise (see also homework)
Ambiguities: Ambiguities: Late Closure and Minimal Late Closure and Minimal AttachmentAttachment
Clause-boundary Ambiguity:Clause-boundary Ambiguity:
– Since Jay always [jogs [a mile]] the race doesn’t Since Jay always [jogs [a mile]] the race doesn’t seem very longseem very long
– Since Jay always jogs [[a mile] doesn’t seem Since Jay always jogs [[a mile] doesn’t seem very long]very long]
In-Class Exercise (see also homework)
Ambiguities: Ambiguities: Late Closure and Minimal Late Closure and Minimal AttachmentAttachment
Reduced Relative-Main Clause Ambiguity:Reduced Relative-Main Clause Ambiguity:
– [The woman [delivered the junkmail on Thursdays]][The woman [delivered the junkmail on Thursdays]]
– [[The woman [delivered the junkmail]] threw it away][[The woman [delivered the junkmail]] threw it away]
In-Class Exercise (see also homework)
Ambiguities: Ambiguities: Late Closure and Minimal Late Closure and Minimal AttachmentAttachment
Relative/Complement Clause Ambiguity:Relative/Complement Clause Ambiguity:
– The doctor [told [the woman [that he was in love with]] [to The doctor [told [the woman [that he was in love with]] [to leave]]leave]]
– The doctor [told [the woman] [that he was in love with her]]The doctor [told [the woman] [that he was in love with her]]
In-Class Exercise (see also homework)
Garden-Path ModelGarden-Path Model
Strengths:Strengths: Considers our working memory Considers our working memory
capacitycapacity Speed achieved by considering one Speed achieved by considering one
interpretationinterpretation Explains broad range of phenomenaExplains broad range of phenomena
Models of Sentence Models of Sentence ProcessingProcessing Garden-Path ModelGarden-Path Model
– AutonomousAutonomous Late closureLate closure Minimal attachmentMinimal attachment
Constraint-Based ModelConstraint-Based Model– InteractiveInteractive
Lexical BiasesLexical Biases Referential ContextsReferential Contexts Structural BiasesStructural Biases }
Cues from multiple sourcesconstrain interpretation
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