looking ahead remaining topics to be covered remaining topics to be covered –meanings and concepts...

Looking AheadLooking Ahead

Remaining topics to be coveredRemaining topics to be covered– Meanings and ConceptsMeanings and Concepts– Pragmatics and Language in UsePragmatics and Language in Use

November 20November 20thth attendance (2 attendance (2ndnd lecture) lecture)

– Language AcquisitionLanguage Acquisition– Bilingualism & Second Language AcquisitionBilingualism & Second Language Acquisition– Evolution of languageEvolution of language

One lectureOne lecture One seminar – Discussion of ReadingsOne seminar – Discussion of Readings

– Relationship between Language and ThoughtRelationship between Language and Thought

Looking AheadLooking Ahead

Reading Homework for SeminarReading Homework for Seminar December 13th December 13th

– Hauser, Chomsky, & Fitch, W. T. Hauser, Chomsky, & Fitch, W. T. (2002).(2002).

– Pinker & Jackendoff (2005)Pinker & Jackendoff (2005)– Fitch, Hauser, & Chomsky (2005)Fitch, Hauser, & Chomsky (2005)– Jackendoff & Pinker (2005)Jackendoff & Pinker (2005)

Psy1302 Psy1302 Psychology of Psychology of LanguageLanguage

Lecture 15Lecture 15

Words and MeaningsWords and Meanings

What are we transmitting What are we transmitting with language???with language???

What are we What are we transmitting with transmitting with language???language??? Language is a means for transmitting Language is a means for transmitting

ideas and concepts…ideas and concepts…

Words represent concepts… Words represent concepts…

How do we represent meanings of words?How do we represent meanings of words?

How do word meanings (concepts) relate How do word meanings (concepts) relate to each other?to each other?

How do we know what the word refers to?How do we know what the word refers to?

How do we learn the word meanings?How do we learn the word meanings?

Hodge-Podge of Difficult Hodge-Podge of Difficult Questions…Questions…

ConceptsConcepts

A word denotes a concept Word meaning (lexical concepts) Combination of words could get

you more complex concepts Categorization = psychological

application of a concept

Theories of ConceptsTheories of Concepts

Meaning as Reference Meaning as Ideas

Classical Theory of Concepts – (Defining Features Representation)

Prototype Theory – (Probabilistic Feature Representation)

Dual Theory – (Both Classical and Prototype)

Theory Theory of Concepts – (Theory-based representations)

These theories differ mostly in what they consider the structure of concepts to be

Hypothesis 1: Hypothesis 1: Meaning as referenceMeaning as reference Child: What’s a fish?Child: What’s a fish? Adult: That’s a fish.Adult: That’s a fish.

Hypothesis 1: Hypothesis 1: Meaning as referenceMeaning as reference

Meaning = ReferenceMeaning = Reference The meaning of a word (or phrase) The meaning of a word (or phrase)

is whatever it refers to in the worldis whatever it refers to in the world– George Washington =George Washington =

a particular persona particular person

– Fish = a kind of animalFish = a kind of animal

– Red = property ofRed = property of

objectsobjects

Hypothesis 1: Hypothesis 1: Meaning as referenceMeaning as referenceProblems?Problems? Words can label non-existing real world referentsWords can label non-existing real world referents

– The Crown Prince of Massachusetts The Crown Prince of Massachusetts – unicornunicorn

Words can refer abstract referentsWords can refer abstract referents– InfinityInfinity– InevitabilityInevitability

Hypothesis 1: Hypothesis 1: Meaning as referenceMeaning as referenceProblems?Problems? Same referent, different meaningSame referent, different meaning

– Morning starMorning star (the last visible star in the eastern sky as dawn (the last visible star in the eastern sky as dawn breaks)breaks)

– Evening starEvening star (the first star visible in the western sky as sun (the first star visible in the western sky as sun sets)sets)

– Creatures with a heartCreatures with a heart– Creatures with a kidneyCreatures with a kidney

Learning: Many non-encountered instancesLearning: Many non-encountered instances– FishFish??

Hypothesis 2: Hypothesis 2: Ideation TheoryIdeation Theory

Words denote ideas rather than objectsWords denote ideas rather than objects

John Locke (1690, p. 225).John Locke (1690, p. 225).– Words in their primary and immediate signification Words in their primary and immediate signification

stands for nothing stands for nothing but the ideas in the mind of him that but the ideas in the mind of him that uses themuses them..

Words allow us to talk about both imaginary and Words allow us to talk about both imaginary and real objectsreal objects– The Crown Prince of Massachusetts The Crown Prince of Massachusetts – UnicornUnicorn

Potential problem: Potential problem: if words make no link to things in the world, how if words make no link to things in the world, how do we know our word meanings are the same as do we know our word meanings are the same as other peoples? other peoples?

Hypothesis 3: Hypothesis 3: Definitional theoryDefinitional theory Meanings are definitional.Meanings are definitional.

Classical Theory of Concepts (Defining Features)

Hypothesis 3: Hypothesis 3: Definitional theoryDefinitional theory

The Classical TheoryThe Classical Theory Word meanings are a set of properties that Word meanings are a set of properties that

are are necessarynecessary and and sufficientsufficient for for membership in the category.membership in the category.

– Meanings are analyzable into bundles of semantic Meanings are analyzable into bundles of semantic primitives (features).primitives (features).

– Triangle: a closed, three sided figure, whose angles add Triangle: a closed, three sided figure, whose angles add up to 180 degrees.up to 180 degrees.


The Classical TheoryThe Classical Theory

FishFish

[aquatic][aquatic]

[water-breathing][water-breathing]

[cold-blooded][cold-blooded]

[animal][animal]

[chambered heart][chambered heart]

Word meanings are a set of properties that are necessary and sufficient for membership in the category.


The Classical TheoryThe Classical Theory

BachelorBachelor– # My husband is a bachelor.# My husband is a bachelor.

Bachelor Bachelor UNMARRIED UNMARRIED

– # I met a two-year-old bachelor.# I met a two-year-old bachelor. Bachelor Bachelor ADULT ADULT

– # My sister is a bachelor.# My sister is a bachelor. Bachelor Bachelor MALE MALE

– # My dog Rex is a bachelor.# My dog Rex is a bachelor. Bachelor Bachelor HUMAN HUMAN

Word meanings are a set of properties that are necessary and sufficient for membership in the category.

[UNMARRIED][ADULT][MALE][HUMAN]


What’s nice about this theory?What’s nice about this theory?


Triangle:Triangle: [closed][closed][3-sided][3-sided][figure][figure]

Is this a triangle?

Learning Word Learning Word MeaningMeaning(Empiricist version)(Empiricist version)1.1. Children enter the world with a limited set of Children enter the world with a limited set of

primitive categories (primitive categories (featuresfeatures), given by ), given by neuropsychologyneuropsychology

Eg. RED; SALTY; OBJECT; CAUSEEg. RED; SALTY; OBJECT; CAUSE

2.2. The sounds that label these primitive are learned The sounds that label these primitive are learned through through associationassociation: co-occurrence in space and : co-occurrence in space and time of word with sensory perceptual experience.time of word with sensory perceptual experience.

3.3. Words with complex meanings (not derivable Words with complex meanings (not derivable from a single sensory perceptual system) are from a single sensory perceptual system) are learned as lists of the innate features or through learned as lists of the innate features or through association.association.


Proposal for learning Proposal for learning meaning of the word meaning of the word “red”“red” Retina stimulated by Retina stimulated by

red light – ~700nm red light – ~700nm triggers red receptor triggers red receptor in brainin brain

Simultaneously ear Simultaneously ear stimulated by stimulated by soundwave “red”soundwave “red”

Co-occurrence leads Co-occurrence leads one to associate one to associate sensory category RED sensory category RED with the word “red”. with the word “red”. “red”


Learning Word Learning Word MeaningMeaning(Empiricist version)(Empiricist version)1.1. Children enter the world with a limited set of Children enter the world with a limited set of

primitive categories (primitive categories (featuresfeatures), given by ), given by neuropsychologyneuropsychology

Eg. RED; SALTY; OBJECT; CAUSEEg. RED; SALTY; OBJECT; CAUSE

2.2. The sounds that label these primitive are learned The sounds that label these primitive are learned through through associationassociation: co-occurrence in space and : co-occurrence in space and time of word with sensory perceptual experience.time of word with sensory perceptual experience.

3.3. Words with complex meanings (not derivable Words with complex meanings (not derivable from a single sensory perceptual system) are from a single sensory perceptual system) are learned as lists of the innate features or through learned as lists of the innate features or through association.association.


Proposal for learning a Proposal for learning a more “complex” wordmore “complex” word Several innate categories combine to Several innate categories combine to

make meaning of make meaning of lemonlemon– YellowYellow– SourSour– OvalOval– ObjectObject

If the sound /lemon/ occurs at the If the sound /lemon/ occurs at the same times that these ideas are same times that these ideas are activated, we learn the word “lemon”activated, we learn the word “lemon”


Creating new complex concepts Creating new complex concepts via via Compositional SemanticsCompositional Semantics

Modifier Head Noun

Feature A

Feature AFeature BFeature CFeature D

Example of Semantic CompositionExample of Semantic Composition

NP

Feature BFeature CFeature D


Union of Features

Feature UnionFeature Union

red triangle

red3-sidedclosed figure

red triangles

[red] [3-sided][closed][figure]

[red][3-sided][closed][figure]

NP


Explanatory Power of Explanatory Power of the Classical Theorythe Classical Theory1.1. Explains category membership and its Explains category membership and its

allowable variation in terms of necessary allowable variation in terms of necessary and sufficient featuresand sufficient features

2.2. Allows identification of new candidatesAllows identification of new candidates

3.3. Explains how you learned the meanings of Explains how you learned the meanings of the words in a way that:the words in a way that:

– is grounded in perceptual experienceis grounded in perceptual experience– builds complex entitiesbuilds complex entities


Explanatory Power of Explanatory Power of the Classical Theorythe Classical Theory4.4. Provides descriptions that can support Provides descriptions that can support

semantic compositionalitysemantic compositionality

5.5. Semantic feature can explain relationships Semantic feature can explain relationships between wordsbetween words


Problems?Problems?

Difficulty in coming up with Difficulty in coming up with necessary and sufficient featuresnecessary and sufficient features

Is it always true that category Is it always true that category membership is all or none?membership is all or none?


What is a game?What is a game?(Wittgenstein, 1953)(Wittgenstein, 1953)

Is it always amusing?

Is it always competition?

Is skill required?

Must luck play a role?

BOTTOM-LINEDifficult to come up with necessary features.

Classical Theory of Concepts (Defining Features) – Problem #1: Coming up w/ features!

BACHELOR revisitedBACHELOR revisited

Alfred is an unmarried Alfred is an unmarried adult male, but he has adult male, but he has been living with his girl-been living with his girl-friend for the last 23 yrs. friend for the last 23 yrs. Their relationship is Their relationship is happy and stale. Is Alfred happy and stale. Is Alfred a bachelor?a bachelor?

BACHELOR:




Bernard is an unmarried Bernard is an unmarried adult male, and he does adult male, and he does not have a partner. not have a partner. Bernard is a monk living Bernard is a monk living in a monastery. Is in a monastery. Is Bernard a bachelor?Bernard a bachelor?

BACHELOR:




Charles is a married adult Charles is a married adult male, but he has not seen male, but he has not seen his wife for many years. his wife for many years. Charles is earnestly Charles is earnestly dating, hoping to find a dating, hoping to find a new partner. Is Charles a new partner. Is Charles a bachelor?bachelor?

BACHELOR:



BACHELOR revisitedBACHELOR revisited Donald is a married adult Donald is a married adult

male, but he lives in a male, but he lives in a culture that encourages culture that encourages men to take two wives. men to take two wives. Donald is earnestly Donald is earnestly dating, hoping to find a dating, hoping to find a new partner. Is Donald a new partner. Is Donald a bachelor?bachelor?

BACHELOR:



Labov (1973)Labov (1973)

Categorization Categorization TaskTask– What is this?What is this?

Classical Theory of Concepts (Defining Features) – Problem #2: Category membership?

What is it?What is it?

CUP

BOWL


What is it?What is it?

CUP

BOWL

* DASHED LINE = FOOD CONTEXT (mashed potato)


Some Problems for Classical Some Problems for Classical Theory Theory

Difficulty in coming up with a set of Difficulty in coming up with a set of necessary and sufficient featuresnecessary and sufficient features– E.g. gameE.g. game

Category membership may not be Category membership may not be ALL-OR-NONEALL-OR-NONE– Category boundaries are fuzzy.Category boundaries are fuzzy.

Categories have Categories have graded membershipgraded membership

Classical Theory of Concepts (Defining Features) – Problem #2: Category membership

Quillian’s Teachable Quillian’s Teachable Language ComprehenderLanguage Comprehender

ANIMAL

BIRD

CANARYOSTRICH

FISH

SHARK SALMON

Has skinCan move around

EatsBreaths

Has wingsCan fly

Has feathers

Is Yellow

Can Sing

Digression: Semantic Networks

Verification Process in TLCVerification Process in TLC“Does a cow produce “Does a cow produce Milk?”Milk?”

MammalHas Fur

Has HoovesBovines

Eats Plants

Cow

Produces milk for young

1.1. Start at node (COW)Start at node (COW)

2.2. Fan out through all Fan out through all links.links.

3.3. Unlimited energy Unlimited energy searchsearch


Collins & Quillian (1969)Collins & Quillian (1969)


Test Search Hypothesis of TLC.Test Search Hypothesis of TLC. TRUE OR FALSE:TRUE OR FALSE:

A canary can sing.A robin is a fish.A cow is an animal.A shark has skin.




Test Search Hypothesis of TLC.Test Search Hypothesis of TLC. TRUE OR FALSE:TRUE OR FALSE:

– A canary is a canary. A canary is a canary. (0 steps)(0 steps)– A canary is a bird.A canary is a bird. (1 step)(1 step)– A canary is an animal.A canary is an animal. (2 steps)(2 steps)


Collins & Quillian (1969)Collins & Quillian (1969)Digression: Semantic Networks

Typicality & Strength of AssociationTypicality & Strength of Association(Conrad, 1972; Rips et al., 1973)(Conrad, 1972; Rips et al., 1973)

1. Collect “Property Norms”1. Collect “Property Norms”– What are typical properties of a cow?What are typical properties of a cow?

gives milk, eats grass, has hooves, etc..gives milk, eats grass, has hooves, etc..

2. Do Collins & Quillian Study:2. Do Collins & Quillian Study:– ““A cow gives milk.” (4 Steps) (but more A cow gives milk.” (4 Steps) (but more

typical)typical)– ““A cow has hooves.” (2 Steps!) (but less A cow has hooves.” (2 Steps!) (but less

typical)typical)


Strength of AssociationStrength of Association(Conrad, 1972; Rips et al., (Conrad, 1972; Rips et al., 1973)1973)

RESULTS?RESULTS?– ““A cow gives milk.” A cow gives milk.” FASTFAST

(4 Steps) (but more typical)(4 Steps) (but more typical)

– ““A cow has hooves.” A cow has hooves.” SLOWSLOW (2 Steps!) (but less typical)(2 Steps!) (but less typical)


Hypothesis 4: Hypothesis 4: Prototype TheoryPrototype Theory

Alternative to definitional theory Alternative to definitional theory

Prototype Theory (Probabilistic Features)

Prototype Theory and Prototype Theory and Family ResemblanceFamily Resemblance Categories have Categories have graded graded

membership: membership: Some members of Some members of a category are reliably rated as a category are reliably rated as “better” members than others“better” members than others– Rating taskRating task– Production taskProduction task– Is-A verification taskIs-A verification task– Feature namingFeature naming


Rating of Rating of PrototypicalityPrototypicality

Please rate the following in the category Please rate the following in the category BIRDBIRD

11 22 3 3 4 4 55 6 6 77

Ostrich

Goodmember

Badmember




11 22 3 3 4 4 55 6 6 77

Robin

Goodmember

Badmember




11 22 3 3 4 4 55 6 6 77

Chicken

Goodmember

Badmember




11 22 3 3 4 4 55 6 6 77

Bat

Goodmember

Badmember




11 22 3 3 4 4 55 6 6 77

Wren

Goodmember

Badmember




11 22 3 3 4 4 55 6 6 77

Eagle

Goodmember

Badmember



Robin: 1.1Robin: 1.1 Eagle: 1.2Eagle: 1.2 Wren: 1.4Wren: 1.4 Ostrich: 3.3Ostrich: 3.3 Chicken: 3.8Chicken: 3.8 Bat: 5.8Bat: 5.8


Production TaskProduction Task

In a minute’s time, list as many fruits In a minute’s time, list as many fruits as you can.as you can.

People will generate prototypical fruit People will generate prototypical fruit names earlier on the list (“apple, names earlier on the list (“apple, orange, peach, grapefruit, apricot, orange, peach, grapefruit, apricot, grapes, blueberries, honeydew”)grapes, blueberries, honeydew”)

Correlates with prototypical ratingCorrelates with prototypical rating


Verification TaskVerification Task

Determine whether each sentence is Determine whether each sentence is true or falsetrue or falseE.g.E.g.– A robin is a bird.A robin is a bird.– A chicken is a bird.A chicken is a bird.– An apple is a fruit.An apple is a fruit.– A fig is a fruit.A fig is a fruit.


Verification TaskVerification Task

High FreqHigh Freq Low FreqLow Freq

+Proto+Proto (orange-(orange-fruit)fruit)

(peach-fruit)(peach-fruit)

-Proto-Proto (fig-fruit)(fig-fruit) (coconut-fruit)(coconut-fruit)

Fast

Slow

Moderate

Moderate> >

Finding: Prototypical items categorized faster.


Feature NamingFeature Naming

Task: List all of the features for Task: List all of the features for subordinate categoriessubordinate categories

E.g., FRUIT: apple; lemon; fig.E.g., FRUIT: apple; lemon; fig.


Feature NamingFeature Naming

Findings:Findings:1.1. Necessary and sufficient features DO NOT Necessary and sufficient features DO NOT

emergeemerge

2.2. Prototypical exemplars share more features Prototypical exemplars share more features with other exemplarswith other exemplars


looking ahead remaining topics to be covered remaining topics to be covered –meanings and concepts...

Documents

concepts words

concepts language

word meanings concepts

meanings of words

reference meaning

objects words

theories of concepts

concepts pragmatics