1. PSY 369: Psycholinguistics Mental representations II

2. Oops! Homework #1: question 2d Should be “bank” not “word”

3. Name this picture “dog” “animal” “Labrador” “bird” “wolf” “plant”

4. 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

5. Collins and Quillian (1969) Animal has skin can move around breathes Lexical entry Semantic Features Collins and Quillian Hierarchical Network model Lexical entries stored in a hierarchy Semantic features attached to the lexical entries

6. Collins and Quillian (1969) Animal has skin can move around breathes has fins can swim has gills has feathers can fly has wings Bird Fish Representation permits cognitive economy Reduce redundancy of semantic features

7. Collins and Quillian (1969) Animal has skin can move around breathes Fish has fins can swim has gills Bird has feathers can fly has wings Canary can sing is yellow Ostrich has long legs is fast can’t fly Local level features may contradict higher level features

8. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False An apple is a fruit

9. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False An robin has wings

10. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False A robin is a bird

11. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False A robin is an animal

12. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False A dog has teeth

13. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False A fish has gills

14. Collins and Quillian (1969) Testing the model Semantic verification task An A is a B True/False Use time on verification tasks to map out the structure of the lexicon. An apple has teeth

15. Collins and Quillian (1969) Testing the model SentenceVerification time Robins eat worms 1310 msecs Robins have feathers 1380 msecs Robins have skin 1470 msecs A category size effect: The higher the location of B, the longer the reaction time (“A is a B” or “A has a B”) Participants do an intersection search

16. Collins and Quillian (1969) Animal has skin can move around breathes Bird has feathers can fly has wings Robin eats worms has a red breast Robins eat worms

17. Collins and Quillian (1969) Animal has skin can move around breathes Bird has feathers can fly has wings Robin eats worms has a red breast Robins eat worms

18. Collins and Quillian (1969) Animal has skin can move around breathes Bird has feathers can fly has wings Robin eats worms has a red breast Robins have feathers

19. Collins and Quillian (1969) Animal has skin can move around breathes Bird has feathers can fly has wings Robin eats worms has a red breast Robins have feathers

20. Collins and Quillian (1969) Animal has skin can move around breathes Bird has feathers can fly has wings Robin eats worms has a red breast Robins have skin

21. Collins and Quillian (1969) Animal has skin can move around breathes Bird has feathers can fly has wings Robin eats worms has a red breast Robins have skin

22. Collins and Quillian (1969) Problems with the model Effect may be due to frequency of association “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.

23. Collins and Quillian (1969) Animal has skin can move around breathes Fish has fins can swim has gills Bird has feathers can fly has wings Robin eats worms has a red breast Ostrich has long legs is fast can’t fly

24. Semantic Networks Prototypes: Some members of a category are better instances of the category than others Fruit: Apple vs. pomegranate What makes a prototype? 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

25. 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

26. Semantic Networks street car bus vehicle red Fire engine truck roses blue orange flowers fire house apple pear tulips fruit

27. Semantic Networks Retrieval of information Spreading activation Limited amount of activation to spread Verification times depend on closeness of two concepts in a network

28. Semantic Networks Fire engine truckbusvehiclecar red housefire apple pear fruit roses flowers tulips blue orangestreet

29. Semantic Networks Fire engine truckbusvehiclecar red housefire apple pear fruit roses flowers tulips blue orangestreet

30. Semantic Networks Fire engine truckbusvehiclecar red housefire apple pear fruit roses flowers tulips blue orangestreet

31. Semantic Networks Fire engine truckbusvehiclecar red housefire apple pear fruit roses flowers tulips blue orangestreet

32. Semantic Networks Fire engine truckbusvehiclecar red housefire apple pear fruit roses flowers tulips blue orangestreet

33. Semantic Networks Advantages of Collins and Loftus model Recognizes diversity of information in a semantic network Captures complexity of our semantic representation Consistent with results from priming studies

34. Bock and Levelt (1994) SHEEPGOAT SheepGoat /gout/ / ip/ ipgout N woolmilkanimal Concepts with semantic features Lemmas grammtical features Lexemes morphemes and sounds Phonemes growth gives Is an category

35. Summary slide here