Psy 369 psycholinguistics
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PSY 369: Psycholinguistics. Language Comprehension: Semantic networks. Semantics. Two levels of analysis (and two traditions of psycholinguistic research) Word level (lexical semantics, chapter 11) What is meaning? How do words relate to meaning? How do we store and organize words?

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PSY 369: Psycholinguistics

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Psy 369 psycholinguistics

PSY 369: Psycholinguistics

Language Comprehension:

Semantic networks


Semantics

Semantics

  • Two levels of analysis (and two traditions of psycholinguistic research)

    • Word level (lexical semantics, chapter 11)

      • What is meaning?

      • How do words relate to meaning?

      • How do we store and organize words?

    • Sentence level (compositional semantics) (chapter 12)

      • How do we construct higher order meaning?

      • How do word meanings and syntax interact?


Separation of word and meaning

Separation of word and meaning

  • Words are not the same as meaning

    • Words are symbols linked to mental representations of meaning (concepts)

      • Even if we changed the name of a rose, we would not change the concept of what a rose is

  • Concepts and words are different things

    • Translation argument – we can translate words between languages (even if not every word meaning is represented by a single word)

    • Imperfect mapping - Multiple meanings of words

      • e.g., ball, bank, bear

  • Elasticity of meaning - Meanings of words can change with context

    • e.g., newspaper


Semantics1

Semantics

  • Meaning is more than just associations

Write down the first word you think of in response to that word.

CAT

“Dog”, “mouse”, “hat”, “fur”, “meow”, “purr”, “pet”, “curious”, “lion”

  • You cannot just substitute these words into a sentence frame and have the same meaning.

    • Frisky is my daughter’s ______.

    • Sometimes you get a related meaning, other times something very different.


Semantics2

In the 90’s

Semantics

  • Referential theory of meaning (Frege, 1892)

    • Sense (intension) and reference (extension)

      • “The world’s most famous athlete.”

      • “The athlete making the most endorsement income.”

      • 2 distinct senses, 1 reference

Now

  • Over time the senses typically stay the same, while the references may change


Word and their meanings

Word and their meanings

  • Semantic Feature Lists

    • Decomposing words into smaller semantic attributes/primitives

      • Perhaps there is a set of necessary and sufficient features


Word and their meanings1

Word and their meanings

  • Semantic Feature Lists

    “John is a bachelor.”

  • What does bachelor mean?

    • What if John:

      • is married?

      • is divorced?

      • has lived with the mother of his children for 10 years but they aren’t married?

      • has lived with his partner Joe for 10 years?

  • Suggests that there probably is no set of necessary and sufficient features that make up word meaning

    • (other classic examples “game”“chair”)


Semantics as exemplars

Semantics as Exemplars

  • Instance theory: each concept is represented as examples of previous experience (e.g., Medin & Schaffer, 1978)

    • Make comparisons to stored instances

    • Typically have a probabilistic component

      • Which instance gets retrieved for comparison

dog


Semantics as prototypes

Semantics as Prototypes

  • Prototype theory: store feature information with most “prototypical” instance (Eleanor Rosch, 1975)

Rate on a scale of 1 to 7 if these are good examples of category: Furniture

1) chair

1) sofa

2) couch

3) table

:

:

12) desk

13) bed

:

:

42) TV

54) refrigerator

TV

couch

table

bed

chair

desk

refrigerator


Semantics as prototypes1

Semantics as Prototypes

  • Prototype theory: store feature information with most “prototypical” instance (Eleanor Rosch, 1975)

    • Prototypes:

      • Some members of a category are better instances of the category than others

        • Fruit: apple vs. pomegranate

      • What makes a prototype?

        • Possibly an abstraction of exemplars

        • More central semantic features

          • What type of dog is a prototypical dog?

          • What are the features of it?

        • We are faster at retrieving prototypes of a category than other members of the category


Semantics as prototypes2

Semantics as Prototypes

  • The main criticism of the model

    • The model fails to provide a rich enough representation of conceptual knowledge

      • How can we think logically if our concepts are so vague?

      • Why do we have concepts which incorporate objects which are clearly dissimilar, and exclude others which are apparently similar (e.g. mammals)?

      • How do our concepts manage to be flexible and adaptive, if they are fixed to the similarity structure of the world?

      • If each of us represents the prototype differently, how can we identify when we have the same concept, as opposed to two different concepts with the same label?


Concepts as theories

Concepts as theories

  • A development of the prototype idea to include more structure in the prototype (e.g., Carey, 1985; Keil, 1986)

    • Concepts provide us with the means to understand our world

      • A lot of this work came out of concepts of natural kinds

    • They are not just the labels for clusters of similar things

    • They contain causal/explanatory structure, explaining why things are the way they are

      • Similar to “scientific theories”

    • They help us to predict and explain the world


Lexical access

Lexical access

Factors affecting lexical access

  • Morphological structure

  • Phonological structure

  • Concretness/abstractness

  • Imageability

  • Frequency

  • Semantic priming

  • Role of prior context

  • Lexical ambiguity

  • Grammatical class

  • Some of these may reflex the structure of the lexicon

  • Some may reflect the processes of access from the lexicon


Lexical organization

Meaning based representations

Grammatical based representations

Sound based representations

Lexical organization

  • There may be multiple levels of representation, with different organizations at each level

Today’s focus


Semantic networks

Semantic Networks

  • Semantic Networks

    • Words can be represented as an interconnected network of sense relations

      • Each word is a particular node

      • Connections among nodes represent semantic relationships


Collins and quillian 1969

has fins

has feathers

can swim

Fish

can fly

Bird

has gills

has wings

Collins and Quillian (1969)

Semantic

Features

  • Representation permits cognitive economy

    • Reduce redundancy of semantic features

has skin

Animal

Lexical entry

can move around

breathes

IS A

IS A

  • Collins and Quillian Hierarchical Network model

    • Lexical entries stored in a hierarchy


Collins and quillian 19691

Collins and Quillian (1969)

  • Testing the model

    • Semantic verification task

      • An A is a B True/False

  • An apple has teeth

  • Use time on verification tasks to map out the structure of the lexicon.


Collins and quillian 19692

Collins and Quillian (1969)

  • Testing the model

    SentenceVerification time

    Robins eat worms 1310 msecs

    Robins have feathers 1380 msecs

    Robins have skin 1470 msecs

    • Participants do an intersection search

has skin

Animal

can move around

breathes

has feathers

can fly

Bird

has wings

Robin

eats worms

has a red breast


Collins and quillian 19693

Collins and Quillian (1969)

  • Testing the model

    SentenceVerification time

    Robins eat worms 1310 msecs

    Robins have feathers 1380 msecs

    Robins have skin 1470 msecs

    • Participants do an intersection search

has skin

Animal

can move around

breathes

Robins eat worms

has feathers

can fly

Bird

has wings

Robin

eats worms

has a red breast


Collins and quillian 19694

Collins and Quillian (1969)

  • Testing the model

    SentenceVerification time

    Robins eat worms 1310 msecs

    Robins have feathers 1380 msecs

    Robins have skin 1470 msecs

    • Participants do an intersection search

has skin

Animal

can move around

breathes

Robins have feathers

has feathers

can fly

Bird

has wings

Robin

eats worms

has a red breast


Collins and quillian 19695

Collins and Quillian (1969)

  • Testing the model

    SentenceVerification time

    Robins eat worms 1310 msecs

    Robins have feathers 1380 msecs

    Robins have skin 1470 msecs

    • Participants do an intersection search

has skin

Animal

can move around

breathes

Robins have feathers

has feathers

can fly

Bird

has wings

Robin

eats worms

has a red breast


Collins and quillian 19696

Collins and Quillian (1969)

  • Testing the model

    SentenceVerification time

    Robins eat worms 1310 msecs

    Robins have feathers 1380 msecs

    Robins have skin 1470 msecs

    • Participants do an intersection search

has skin

Animal

can move around

breathes

Robins have skin

has feathers

can fly

Bird

has wings

Robin

eats worms

has a red breast


Collins and quillian 19697

Collins and Quillian (1969)

  • Testing the model

    SentenceVerification time

    Robins eat worms 1310 msecs

    Robins have feathers 1380 msecs

    Robins have skin 1470 msecs

    • Participants do an intersection search

has skin

Animal

can move around

breathes

Robins have skin

has feathers

can fly

Bird

has wings

Robin

eats worms

has a red breast


Collins and quillian 19698

Collins and Quillian (1969)

  • Problems with the model

    • Difficulty representing some relationships

      • How are “truth”, “justice”, and “law” related?

    • Effect may be due to frequency of association

      (organization and conjoint frequency confounded)

      • “A robin breathes” is less frequent than “A robin eats worms”

    • Assumption that all lexical entries at the same level are equal

      • The Typicality Effect

        • A whale is a fish vs. A horse is a fish

        • Which is a more typical bird? Ostrich or Robin.


Collins and quillian 19699

has long legs

Robin

eats worms

Ostrich

is fast

can’t fly

has a red breast

Collins and Quillian (1969)

has skin

Animal

can move around

Robin and Ostrich occupy the same relationship with bird.

breathes

has fins

has feathers

can swim

Fish

can fly

Bird

has gills

has wings

Verification times:

“a robin is a bird” faster than “an ostrich is a bird”


Collins and quillian 196910

Collins and Quillian (1969)

  • Problems with the model

Animal

  • Smith, Shoben & Rips (1974) showed that there are hierarchies where more distant categories can be faster to categorize than closer ones

    • A chicken is a bird

      was slower to verify than

    • A chicken is an animal

has feathers

can fly

Bird

has wings

Chicken

lays eggs

clucks


Spreading activation models

Spreading Activation Models

  • Collins & Loftus (1975)

  • Words represented in lexicon as a network of relationships

  • Organization is a web of interconnected nodes in which connections can represent:

    • categorical relations

    • degree of association

    • typicality

  • street

    vehicle

    car

    bus

    truck

    house

    orange

    Fire

    engine

    fire

    red

    blue

    apple

    pear

    tulips

    roses

    fruit

    flowers


    Spreading activation models1

    Spreading Activation Models

    • Collins & Loftus (1975)

    • Retrieval of information

      • Spreading activation

      • Limited amount of activation to spread

      • Verification times depend on closeness of two concepts in a network

    street

    vehicle

    car

    bus

    truck

    house

    orange

    Fire

    engine

    fire

    red

    blue

    apple

    pear

    tulips

    roses

    fruit

    flowers


    Spreading activation models2

    Spreading Activation Models

    • Advantages of Collins and Loftus model

      • Recognizes diversity of information in a semantic network

      • Captures complexity of our semantic representation (at least some of it)

      • Consistent with results from priming studies


    Spreading activation models3

    Spreading Activation Models

    • More recent spreading activation models

      • Probably the dominant class of models currently used

      • Typically have multiple levels of representations


    Conceptual combination

    Conceptual combination

    • How do we combine words and concepts

      • We can use known concepts to create new ones

        • Noun-Noun combinations

          • Modifier noun

          • Head noun

            “Skunk squirrel”

            “Radiator box”

            “Helicopter flower”


    Conceptual combination1

    Conceptual combination

    • How do we combine words and concepts

      • Relational combination

        • Relation given between head and modifier

        • “squirrel box” a box that contains a squirrel

      • Property mapping combination

        • Property of modifier attributed to head

        • “skunk squirrel” a squirrel with a white stripe on its back

      • Hybrid combinations

        • A cross between the head and modifier

        • “helicopter flower” a bird that has parts of helicopters and parts of flowers


    Conceptual combination2

    Conceptual combination

    • How do we combine words and concepts

      • Instance theory has problems (but see the pictures on last slide)

      • Modification? (brown apple)

      • Separate Prototypes? (big wooden spoon)

        • But sometimes the combination has a prototypical feature that is not typical of either noun individually (pet birds live in cages, but neither pets nor birds do)

      • Extending salient characteristics?

        • When nouns are “alignable” (zebra horse)

        • But non-alignable nouns are combined using a different mechanism (zebra house)


    Figurative language

    Figurative Language

    • Up to this point we have focused on meaning in “literal language”

    • Figurative language uses word in ways that go beyond what is usually considered their typical meaning

      • e.g., metaphors, idioms, sarcasm

    • How is it understood? Do you have to understand a literal meaning and then metaphor? Does it violate communication norms?


    Figurative language1

    Figurative Language

    • Metaphor

      • “a figure of speech in which a word or a phrase literally denoting one kind of object or idea is used in place of another to suggest a likeness or analogy between them” (Kruglanski, Crenshaw, Post, & Victoroff, 2007)


    Figurative language2

    Figurative Language

    • Metaphor

      • Cacciari & Glucksberg (1994): How do you spot them?

        • Syntactic difference? No.

          • The old rock has become brittle with age. (Referring to a professor.)

        • Deviance (e.g., some literal violation is detected)? No.

          • No man is an island. (True and figurative.)

          • My husband is an animal. (True and figurative.)

          • Tom’s a real marine. (Could be true.)


    Figurative language3

    Figurative Language

    • Metaphor

      • Cacciari & Glucksberg (1994): Do you need to go through literal to metaphorical?

        • Sam is a pig.

          • Literal.

          • Assess against context.

          • If literal won’t work, go figurative.

        • Generally no difference in comprehension time for literal and figurative interpretations.

        • Cacciari & Glucksberg argue that literal vs. figurative is better thought of as a continuum rather than as a dichotomy.


    Meaning beyond the word

    Meaning beyond the word

    • Not all meaning resides at the level of the individual words.

      • Conceptual combinations

      • Figurative phrases

      • Sentences

    • Move to compositional semantics


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