Psy1302 Psychology of Language

1. Psy1302 Psychology of Language Lecture 10 Ambiguity Resolution Sentence Processing I

2. agenda • Connecting word recognition with sentence processing via ambiguity resolution. • Lexical Ambiguity • Syntactic Ambiguity • & MORE MODELS!!! • Garden-Path Model • Constraint-Satisfaction Model • & CLEVER but difficult to explain experiments! (so ask questions if you are lost!!!)

3. Ambiguity Time flies like an arrow • Time proceeds as quickly as an arrow proceeds. • Measure the speed of flies in the same way that you measure the speed of an arrow. • Measure the speed of flies in the same way that an arrow measures the speed of flies. • Measure the speed of flies that resemble an arrow. • Flies of a particular kind, time flies, are fond of an arrow.

4. Qs about Online Ambiguity Resolution • What alternatives are available at different time points? • What degree of commitment is made to one or more alternatives? • What information is used to guide these commitments?

5. Lexical Ambiguity(semantic, lexical)

6. Cross-Modal Priming

7. Cross-Modal Priming Exp. 1(Swinney et al. 1978; Onifer & Swinney, 1981) Rumour had it that for many years, the government building had been plagued with problems. The man was not surprised when he found several (spiders, roaches, and other) bugs in the corner of his room. { ANT ANT SPY SPY SEW SEW

8. Cross-Modal Priming Exp. 1(Swinney et al. 1978; Onifer & Swinney, 1981) 80 70 “ant” 60 “spy” 50 Amount of Priming (unrelated word RT minus related word RT) 40 30 20 10 0 immediate 3 syll delay

9. Cross-Modal Priming Exp. 1(Swinney et al. 1978; Onifer & Swinney, 1981) Rumour had it that for many years, the government building had been plagued with problems. The man was not surprised when he found several (spiders, roaches, and other) bugs (insects) in the corner of his room. { ANT ANT SPY SPY SEW SEW

10. Riddle • What has wheels and flies, but is not an airplane? • What [has wheels] and [flies], but is not an airplane? • What has [wheels and flies], but is not an airplane? V N

11. Cross-Modal Priming Exp. 2(Tanenhaus, Leiman, & Seidenberg, 1979; Seidenberg, Tanenhaus, Leiman, & Bienkowski, 1982) • Noun reading: I bought a watch. • Verb reading: I will watch. 0 600 200 CLOCK 0 600 200 CLOCK

12. Cross-Modal Priming Exp. 2(Tanenhaus, Leiman, & Seidenberg, 1979; Seidenberg, Tanenhaus, Leiman, & Bienkowski, 1982) • Noun reading: I bought a watch. • Verb reading: I will watch. 0 600 200 clock clock clock 0 600 200 clock clock clock

13. Effects of Frequency in Ambiguity Resolutions Non-Equibias Ambiguous Word Equibias Ambiguous Word port pitcher

14. Duffy, Morris, & Rayner (1988) • Varied frequency of homonyms • Varied whether supportive context came before word or after word.

15. Older Eye-tracker • low-level infrared light  eye • reflections from cornea and lens indicate position of eye fixation. • Head movements messes up calibration •  Bite bar or head rest is needed

16. Duffy, Morris, & Rayner (1988) Supportive Context No Supportive Context Supportive Context No Supportive Context *Control words in Parentheses *For Non-Equibiased, Context supports non-dominant reading.

17. No Supportive Context Non-Ambiguous Control Equibias Ambiguous Word pitcher whiskey Non-Ambiguous Control Non-Equibias Ambiguous Word soup port -- Thickness of the line indicates amount of activation.

18. + supportive context + supportive context Adding Supportive Context Non-Ambiguous Control Equibias Ambiguous Word pitcher whiskey Non-Ambiguous Control Non-Equibias Ambiguous Word soup port -- Thickness of line indicates amount of activation.

19. Supportive Context No Supportive Context Equibias + supportive context pitcher Non-Equibias port + supportive context

20. = High reaction time Supportive Context No Supportive Context • Equibiased: • Processing time lower when provided with prior disambiguating contextual support. (Reason: because accessing both meanings) • Non-equibiased: • Processing time high when provided with prior disambiguating contextual support supporting the less frequent meaning. (Reason: made the less frequent more “equal” to the other meaning) • Processing time low when not provided disambiguating contextual support for the less frequent meaning. (Reason: not considering the less frequent meaning. In fact, time spent later in disambiguating region is higher due to a need to reanalyze).

21. Lexical Ambiguity Current conclusions • Parallel, rather than serial activation • Relative strength of activation depends on: • Degree of contextual constraint available • Frequency of use of each meaning

22. Syntax • Another level up! • Parsing: figuring how the words in a phrase or sentence combine, using the rules in a grammar. • Parser

23. Syntactic Ambiguity

24. Is the woman insured? • Woman drives off with what she thought was her date’s car (but wasn’t) and then totaled it. Can she get money from her insurance company: • Contract says: • Such insurance as is provided by this policy applies to the use of a non-owned vehicle by the named insured and any person responsible for use by the named insured provided such use is with the permission of the owner.

25. Does he deserve jail time? • Drug dealer tried to swindle an (unbeknownst to him) undercover cop by selling a bag of powder that had only a minuscule trace of methamhetamine. The quantity was not harmful. • Law says • Every person who sells any controlled substance which is specified in subdivision (d) shall be punished. • (d) Any material, compound, mixture, or preparation which contains any quantity of the following substance having a potential abuse associated with a stimulant effect on the central nervous system: Amphetamine, Methamphetamine…

26. The bully hit the girl with the... ...stick. ...wart.(*garden-pathed) The woman felt the fur... ...and then left. ...was very expensive. (*garden-pathed) Local Ambiguities (Being led down the “garden-path”)

27. Local Ambiguities • The bully hit the girl with the wart and then… • The bully hit the girl with the stick and then…

28. Homework sentence The reporter said the car crashed last night. Ambiguous Sentences Last night, the car crashed. The car crashed. yesterday today yesterday today time time

29. The reporter said the car crashed last night. …car... …car.... time S time VP NP VP NP S V AdvP S said The reporter V VP NP said VP NP last night AdvP V the car V crashed the car last night crashed Ambiguous Sentences S The reporter

30. Homework sentence Jamie saw the man with the telescope. Ambiguous Sentences

31. Jamie saw the man with the telescope. S VP NP NP PN PP V saw Jamie Det N P NP with the man S the telescope VP NP NP PN V saw Jamie NP PP Det N NP P the man with the telescope Ambiguous Sentences

32. Traditional Views(contrasting lexical and syntactic ambiguity) Table from MacDonald, Pearlmutter, & Seidenberg Paper

33. Garden-Path Model(Frazier & Fodor, 1978) • Serial: the processor initially identifies only one analysis • selected based on structural simplicity • Modular: Initial structure built on the basis of syntactic category labels. • revision process incorporates other information.

34. Garden Path ModelSelecting the initial analysis • When word is identified, its syntactic category is retrieved • Parser identifies which rules of the grammar contain that category • Analysis selected on the basis of structural simplicity • Late Closure • Minimal Attachment

35. Garden Path ModelHeuristics for Simplicity • Late Closure • When possible, attach incoming lexical items into the clause or phrase currently being processed (i.e., the lowest possible nonterminal node dominating the last item analyzed). • Minimal Attachment • Attach incoming lexical items into the phrase-marker being constructed with the fewest nodes consistent with well-formedness rules of language.

36. S VP NP AdvP S V The reporter said NP VP last night V S the car crashed VP NP ..car… ..car… S The reporter V said NP VP yesterday today yesterday today AdvP V time the car crashed time last night Late Closure

37. S VP NP The reporter V said NP VP AdvP V the car crashed last night Late Closure crashed The reporter said the car last night 1 or 2? 1 2 S

38. Last night… time S VP NP VP NP S V AdvP S said The reporter V VP NP said VP NP last night AdvP V the car V crashed the car last night crashed Late Closure • Choice #1 • Choice #2 S The reporter …car...

39. S VP NP NP PN PP V saw Jamie Det N P NP with the man S the telescope VP NP NP PN V saw Jamie NP PP Det N NP P the man with the telescope Minimal Attachment

40. NP PN Jamie S VP V PP NP saw N Det P with man the Minimal Attachment Jamie saw man with the 1 or 2? 1 2

41. NP NP PN PN Jamie Jamie S S VP VP PP V V NP saw saw P with N N Det man man the Minimal Attachment • Choice #1 • Choice #2 NP  Det + N NP  NP + PP NP 1 extra node NP Det the PP P with

42. Garden Path ModelHeuristics for Simplicity • Late Closure • When possible, attach incoming lexical items into the clause or phrase currently being processed (i.e., the lowest possible nonterminal node dominating the last item analyzed). • Minimal Attachment • Attach incoming lexical items into the phrase-marker being constructed with the fewest nodes consistent with well-formedness rules of language.

43. NP/VP Attachment Ambiguity: The cop [saw [the burglar] [with the binoculars]] The cop saw [the burglar [with the gun]] In-Class Exercise (see also homework) Ambiguities: Late Closure and Minimal Attachment

44. NP/S Complement Attachment Ambiguity: The athlete [realized [his goal]] last week The athlete realized [[his shoes] were across the room] In-Class Exercise (see also homework) Ambiguities: Late Closure and Minimal Attachment

45. Clause-boundary Ambiguity: Since Jay always [jogs [a mile]] the race doesn’t seem very long Since Jay always jogs [[a mile] doesn’t seem very long] In-Class Exercise (see also homework) Ambiguities: Late Closure and Minimal Attachment

46. Reduced Relative-Main Clause Ambiguity: [The woman [delivered the junkmail on Thursdays]] [[The woman [delivered the junkmail]] threw it away] In-Class Exercise (see also homework) Ambiguities: Late Closure and Minimal Attachment

47. Relative/Complement Clause Ambiguity: The doctor [told [the woman [that he was in love with]] [to leave]] The doctor [told [the woman] [that he was in love with her]] In-Class Exercise (see also homework) Ambiguities: Late Closure and Minimal Attachment

48. Garden-Path Model Strengths: • Considers our working memory capacity • Speed achieved by considering one interpretation • Explains broad range of phenomena

49. Models of Sentence Processing • Garden-Path Model • Autonomous • Late closure • Minimal attachment • Constraint-Based Model • Interactive • Lexical Biases • Referential Contexts • Structural Biases } Cues from multiple sources constrain interpretation

50. Traditional Views(contrasting lexical and syntactic ambiguity) Constraint-Satisfaction Model SAYS it’s not the right characterization! Table from MacDonald, Pearlmutter, & Seidenberg Paper