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Presentation on theme: "Announcements Sample exam questions Sample exam questions –This week (Thursday): You will submit your Qs into dropbox Bring Completed Homework Bring Completed."— Presentation transcript:

1 Announcements Sample exam questions Sample exam questions –This week (Thursday): You will submit your Qs into dropbox Bring Completed Homework Bring Completed Homework –For next class: sentence completion survey given to friends.

2 Psy1302 Psychology of Language Lecture 11 & 12 Sentence Comprehension II

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

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

5 Experiment to test the 2 models (Tanenhaus, Spivey-Knowlton, Eberhard, & Sedivy, 1995) Method: Eye-Tracking During Listening

6 Group 1 Putthefrogonthenapkininthebox. Setting-Up the Experiment: RC

7 Group 2 Putthefrogonthenapkininthebox.thatis Setting-Up the Experiment: RC

8 Which group was garden-pathed? Group 1: Group 1: Put the frog on the napkin in the box. Group 2: Group 2: Put the frog that is on the napkin in the box. Setting-Up the Experiment: RC

9 What is a Relative Clause? Relative Clause: a subordinate clause that modifies the noun Relative Clause: a subordinate clause that modifies the noun Group 1: Group 1: Put the frog on the napkin in the box. Group 2: Group 2: Put the frog that is on the napkin in the box. REDUCED RELATIVE CLAUSE, AMBIGUOUS AT “ON” NON-REDUCED RELATIVE CLAUSE, UNAMBIGUOUS AT “ON” Setting-Up the Experiment: RC

10 Garden-Path Model How does the model explain the difficulty of parsing: How does the model explain the difficulty of parsing: Put the frog on the napkin in the box. The sentence processed using these 2 simple rules: The sentence processed using these 2 simple rules: –Late Closure & Minimal Attachment Sometimes these simple rules lead leads one down the incorrect path, and a reanalysis is necessary. Sometimes these simple rules lead leads one down the incorrect path, and a reanalysis is necessary. Setting-Up the Experiment: Garden-Path

11 frog VP NPV put the Det N PP on P Where to attach? Late Closure 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 Minimal Attachment –Attach incoming lexical items into the phrase-marker being constructed with the fewest nodes consistent with well-formedness rules of language. Setting-Up the Experiment: Garden-Path VP or NP? put the frog on… VP-attachment NP-attachment

12 2 Attachments & 2 Meanings VP attachment VP attachment NP attachment NP attachment VP NP PP V put thefrog on NP Det N P thenapkin Det N VP NP PP V put thefrogon NPDet NP thenapkin Det N NP … the frog (that is) on the napkin… PP phrase as modifier of “frog” Setting-Up the Experiment: Garden-Path PP phrase as destination of “put” the frog on(to) the napkin put

13 frog VP NPV put the Det N PP on P Where to attach? Late Closure 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 Minimal Attachment –Attach incoming lexical items into the phrase-marker being constructed with the fewest nodes consistent with well-formedness rules of language. 1. CANNOT attach directly to NP: NP  Det N PP IF attach to NP: NP  NP PP  Violates Minimal Attachment! 2. Attach to VP: VP  V NP PP Does NOT violate either rules! Setting-Up the Experiment: Garden-Path VP-attachment NP-attachment VP or NP?

14 Garden-Path Model How does the model explain the difficulty of parsing: How does the model explain the difficulty of parsing: Put the frog on the napkin in the box. Answer: Answer: Setting-Up the Experiment: Garden-Path put the frog on the napkin in… 2. When encountering the 2 nd prep “in” of “in the box”, parser does not know how to incorporate the word. put the frog on… 1. Syntactic processor first VP-attaches for “on” 1. Syntactic processor first VP-attaches for “on” 3. Reanalysis is needed due to incorrect first parse  longer processing time.

15 Constraint-Satisfaction Model How does the model explain the difficulty of parsing: How does the model explain the difficulty of parsing: Put the frog on the napkin in the box. Constraint-Satisfaction Model uses information from multiple sources to constrain interpretation Constraint-Satisfaction Model uses information from multiple sources to constrain interpretation –In this case the lexical and contextual information likely does not support the interpretation or favors another one. Setting-Up the Experiment: Garden-Path

16 Constraint-Satisfaction Model How does the model explain the difficulty of parsing: How does the model explain the difficulty of parsing: Put the frog on the napkin in the box. BIG Q: What kinds of information can be used to constrain interpretation? BIG Q: What kinds of information can be used to constrain interpretation?Examples: –Lexical Biases –Referential Context Setting-Up the Experiment: Constraint-Satisfaction Model

17 Constraint-Satisfaction Model Lexical Biases Type of syntactic/semantic environments in which a word appears Type of syntactic/semantic environments in which a word appearsExample: –“Put” almost always appears with a VP attached PP (destination) “Put the car in the garage” “Put the car in the garage” –“Choose” rarely does so “Choose the car in the garage” “Choose the car in the garage” Setting-Up the Experiment: Constraint-Satisfaction Model

18 Constraint-Satisfaction Model How does the model explain the difficulty of parsing: How does the model explain the difficulty of parsing: Put the frog on the napkin in the box. Lexical Biases Support VP-attachment Lexical Biases Support VP-attachment –“Put” almost always appears with a VP attached PP (destination) –“on” is a locative preposition “on the napkin” is a location “on the napkin” is a location i.e., compatible with possibility of a destination required by “put” i.e., compatible with possibility of a destination required by “put” Setting-Up the Experiment: Constraint-Satisfaction Model

19 Constraint-Satisfaction Model Referential Context Referential Context –Pick a frog. –Which frog did you pick? –Modifiers pick out a member of a set When 2+ referents, modifiers help differentiate the referent in question When 2+ referents, modifiers help differentiate the referent in question Setting-Up the Experiment: Constraint-Satisfaction Model

20 Experiment to test the 2 models (Tanenhaus, Spivey-Knowlton, Eberhard, & Sedivy, 1995) FINALLY, the experiment!!! FINALLY, the experiment!!! Do we consider the referential context in parsing? Do we consider the referential context in parsing? More specifically, WHEN do we consider referential parsing? More specifically, WHEN do we consider referential parsing? http://www.ircs.upenn.edu/Trueswellabs/video.html

21 Do we consider the referential context in parsing? Do we consider the referential context in parsing? More specifically, WHEN do we consider referential parsing? More specifically, WHEN do we consider referential parsing? 1-Referent: 1 frog 2-Referents: 2 frogs Putthefrogonthenapkininthebox. OR

22 Do we consider the referential context in parsing? Do we consider the referential context in parsing? More specifically, WHEN do we consider referential parsing? More specifically, WHEN do we consider referential parsing? 1-Referent: 1 frog 2-Referents: 2 frogs Putthefrogonthenapkininthebox. OR NAPKIN is a potential destination.

23 Do we consider the referential context in parsing? Do we consider the referential context in parsing? More specifically, WHEN do we consider referential parsing? More specifically, WHEN do we consider referential parsing? 1-Referent: 1 frog 2-Referents: 2 frogs Putthefrogonthenapkininthebox. OR BY GARDEN-PATH MODEL: Regardless of 1 or 2 referent, during the first pass, NAPKIN is considered as a destination.

24 Do we consider the referential context in parsing? Do we consider the referential context in parsing? More specifically, WHEN do we consider referential parsing? More specifically, WHEN do we consider referential parsing? 1-Referent: 1 frog 2-Referents: 2 frogs Putthefrogonthenapkininthebox. OR BY CONSTRAINT-SATISFACTION MODEL (which takes into consideration of referential context early): For 1 referent, NAPKIN is considered as a destination For 2 referent, NAPKIN could potentially be a modifier of FROG, and NOT a destination

25 Tanenhaus, Spivey-Knowlton, Eberhard, & Sedivy (1995) Method: Eye-Tracking During Listening Put the frog on the napkin… into the box. (1-Referent) (2-Referents) Put the frog that is on the napkin… into the box. (1-Referent) (2-Referents) AMBIGUOUS SENTENCE HEARD: UNAMBIGUOUS SENTENCE HEARD:

26 CORRECT DESTINATION INCORRECT DESTINATION PUT THE FROG ON THE NAPKIN IN THE BOX. - Unreduced Relative “that is” - Reduced Relative

27 2 3 1 4 1-Referent: 1 frog 2-Referents: 2 frogs Putthefrogonthenapkininthebox. 1 2 34 Typical Eye-movement for the Ambiguous Sentences

28 1 2 3 4 A B 1-Referent: 1 frog 2-Referents: 2 frogs Putthefrogonthenapkininthebox. 1 2 34 Typical Eye-movement for the Ambiguous Sentences AB

29 Typical Eye-movements Figures from Tanenhaus et al. (1995)

30 Constraint-Satisfaction Model Highly Interactive Highly Interactive Limited Parallel Processing Limited Parallel Processing –If all information converge on a single analysis, then serial –If they do not, then several may be maintained

31 How are cues combined? (Interactive Activation Unfolding in Time) Verb Argument Structure (prob. of PP) e.g., put, choose Preposition prob. of NP vs. VP e.g., of, on Noun Arg Structure (prob. of PP) e.g., frog PP VP-Attached PP NP-Attached Referential Context or

32 How are cues combined? (Interactive Activation Unfolding in Time) Selection of VP- vs. NP-attachment Selection of VP- vs. NP-attachment –Put the frog on… When with: When with: –1 referent –2 referent Verb Argument Structure (prob. of PP) e.g., put, choose Preposition prob. of NP vs. VP e.g., of, on Noun Arg Structure (prob. of PP) e.g., frog Referential Context or NP-Attachment VP-Attachment

33 How are cues combined? (Interactive Activation Unfolding in Time) Preposition prob. of NP vs. VP e.g., of, on Noun Arg Structure (prob. of PP) e.g., frog PP VP-Attached PP NP-Attached Referential Context or PUT (V): NP, PP

34 How are cues combined? (Interactive Activation Unfolding in Time) Preposition prob. of NP vs. VP e.g., of, on Noun Arg Structure (prob. of PP) e.g., frog PP VP-Attached PP NP-Attached Referential Context or PUT (V): NP, PP

35 How are cues combined? (Interactive Activation Unfolding in Time) Preposition prob. of NP vs. VP e.g., of, on PP VP-Attached PP NP-Attached Referential Context or PUT (V): NP, PP FROG (N): No bias

36 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context or PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach.

37 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context or PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach.

38 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context or PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach.

39 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach. 1-referent

40 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach. 1-referent

41 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach. 2-referents

42 How are cues combined? (Interactive Activation Unfolding in Time) PP VP-Attached PP NP-Attached Referential Context PUT (V): NP, PP FROG (N): No bias ON (P): 95% NP-Attach 5% VP-Attach. 2-referents

43 Break!

44 Moving on to Assigned Readings Garden Path Model vs. Constraint Satisfaction Model Garden Path Model vs. Constraint Satisfaction Model –Ferreira & Clifton (1986) –Trueswell, Tanenhaus, & Garnsey (1994)

45 Subtext These experiments test hypotheses These experiments test hypotheses –What was being tested? –What was found? Multiple experiments Multiple experiments –How did each experiment replicate or extend previous findings? –How did each experiment support or refute previous findings?

46 Outline Stats Terms Simplified Stats Terms Simplified –t-tests –ANOVAs, Main effects and Interactions –Regressions, Correlations Assigned Papers Assigned Papers

47 T-tests and ANOVAs T-tests: Compare 2 means. T-tests: Compare 2 means. ANOVA (Analysis of Variance): Compare multiple means ANOVA (Analysis of Variance): Compare multiple means –Yields significance of main or interaction effects

48 Hypothetical Experiment (Example of Main & Interactions Effects) Dependent Measure: Number of Girlfriends Dependent Measure: Number of Girlfriends Independent Measure: Independent Measure: –Wealth of bachelors according to Income (Rich, Poor) (Rich, Poor) –Looks of same bachelors according to Oprah (Handsome, Ugly) (Handsome, Ugly)

49 Design 2 x 2 RichPoor Hand-some Ugly # of GF

50 RichPoor Hand- some Ugly RichPoor Ugly Few Many Few Many Few RichPoor Hand- some Ugly RichPoor Ugly Many Least Most Many Few Many RichPoor #GFs handsome ugly RichPoor #GFs ugly handsome RichPoor #GFs handsome ugly RichPoor #GFs ugly handsome

51 Hypothetical Experiment (Example of ANOVAs F1 vs. F2) Is a female model more attractive in short or long skirt? Is a female model more attractive in short or long skirt? – Model pictured in 10 different short skirts and 10 different long skirts –30 Males rated the model’s attractiveness in each skirt (1 = not attractive to 7 = extremely attractive)

52 Hypothetical Experiment (Example of ANOVAs F1 vs. F2) F1: Subject Analysis F1: Subject Analysis –Comparing subjects –Averaging across items for each subject F2: Items Analysis F2: Items Analysis –Comparing items –Averaging across subjects for each item

53 Hypothetical Experiment (Example of ANOVAs F1 vs. F2) F1: Subject Analysis F1: Subject Analysis F2: Items Analysis F2: Items Analysis ShortLong Frederick H.5.23.1 Hef7.07.0 Rudy G.5.24.9 Bill C.6.91.3 Rating Short Skirt 14.5 Short Skirt 25.3 … Long Skirt 16.7 Long Skirt 23.5 …

54 Correlations Regression Regression Correlation: Correlation: –degree of association between two random variables. Partial correlation: Partial correlation: –degree of association between two random variables, with the effect of a set of controlling random variables removed. -1 ≤ R ≤ 1 -1 ≤ R ≤ 1 –Positive correlation –Negative correlation –No correlation

55 Ferreira & Clifton (1986) Q: Is the initial syntactic processing stage influenced by: 1. thematic/semantic information (Exp. 1) 2. pragmatic or contextual information (Exp. 2 & 3) A: No, according to Garden-Path Model. Autonomous/modular parser. Context information is used only after initial parse. Goal of Experiments: To experimentally test (and provide evidence) for such a position.

56 Thematic Roles Terminologies Thematic Roles and Argument Structure: Thematic Roles and Argument Structure: Thematic role is the semantic relationship between a predicate (e.g. a verb) and an argument (e.g. the noun phrases) of a sentence. Thematic role is the semantic relationship between a predicate (e.g. a verb) and an argument (e.g. the noun phrases) of a sentence.

57 Thematic Roles (examples) Courtney hit the ball with the bat to Richard. Courtney hit the ball with the bat to Richard. Verb: Hit Verb: Hit Instrument Patient Goal Agent

58 Thematic Roles (more examples) Agent: deliberately performs the action (e.g. Bill ate his soup quietly) Agent: deliberately performs the action (e.g. Bill ate his soup quietly) Experiencer: receives sensory or emotional input (e.g. Bill slept). Experiencer: receives sensory or emotional input (e.g. Bill slept). Theme/Patient: undergoes the action (e.g. The rocks crushed the car). Theme/Patient: undergoes the action (e.g. The rocks crushed the car). Instrument: used to carry out the action (e.g. He hit her with a stick). Instrument: used to carry out the action (e.g. He hit her with a stick). Cause: mindlessly performs the action (e.g. An avalanche destroyed the ancient temple). Cause: mindlessly performs the action (e.g. An avalanche destroyed the ancient temple). Location: where the action occurs (e.g. I put the car in the garage). Location: where the action occurs (e.g. I put the car in the garage). Goal: what the action is directed towards (e.g. I moved to Boston). Goal: what the action is directed towards (e.g. I moved to Boston). Source: where the action originated (e.g. I came from Harvard Square). Source: where the action originated (e.g. I came from Harvard Square). From WIKIPEDIA

59 Animacy Animacy pertains to likelihood the noun refers to an animate being, and thus is likely to be an agent (i.e., performer of an action). Animacy pertains to likelihood the noun refers to an animate being, and thus is likely to be an agent (i.e., performer of an action). Animate vs. Inanimate. Animate vs. Inanimate. Inanimate Animate

60 Animate: defendant Animate: defendant –Defendant = a good agent The defendant examined by the lawyer turned out to be unreliable. Inanimate: evidence Inanimate: evidence –Evidence = not a good agent (but possibly good theme/patient) The evidence examined by the lawyer turned out to be unreliable. Animacy

61 Relative Clause: Reduced vs. Unreduced Reduced Relative Clause Reduced Relative Clause The defendant examined (by the lawyer) turned out to be unreliable. Unreduced Relative Clause Unreduced Relative Clause The defendant who was examined (by the lawyer) turned out to be unreliable. Ambiguous at “examined” Unambiguous at “examined”

62 Main Clause vs. Reduced Relative Clause “ The defendant examined …” is ambiguous at “ examined ” because the sentence has 2 possible continuations: “ The defendant examined …” is ambiguous at “ examined ” because the sentence has 2 possible continuations: Possibility 1: Main Clause Reading “ examined ” is the verb of the MAIN sentence. e.g. The defendant examined the lawyer. Possibility 2: Reduced Relative Clause Reading “ examined ” is the verb of the RELATIVE clause. e.g. The defendant examined by the lawyer turned out to be unreliable.

63 Main Clause vs. Reduced Relative Clause Possibility 1: Main Clause Reading Possibility 1: Main Clause Reading “ defendant ” is the agent examining something [S[NP The defendant [VP examined … Possibility 2: Reduced Relative Clause Reading Possibility 2: Reduced Relative Clause Reading “ defendant ” is the patient being examined [S[NP[NP The defendant [RC examined … Easier by Garden-Path Model “The defendant examined…”

64 Design (Is there early thematic/semantic influence?) 4 Sentence Types: Reduced, Animate Reduced, Animate The defendant examined by the lawyer turned out to be unreliable. Reduced, Inanimate Reduced, Inanimate The evidence examined by the lawyer turned out to be unreliable. Unreduced, Animate Unreduced, Animate The defendant that was examined by the lawyer turned out to be unreliable. Unreduced, Inanimate Unreduced, Inanimate The evidence that was examined by the lawyer turned out to be unreliable. DISAMBIGUATING REGION

65 F&C: Experiment 1 the influence of thematic information ANIMATE(A)INANIMATE(I) Reduced Relative (RR) RR-A RR-I Unreduced Relative(UR) UR-A UR-I ANIMACY SENTENCE TYPE

66 The Measurement and Scoring Regions Measures fixation time in regions Measures fixation time in regions –First pass: first left to right fixation on the region & right-to-left movement within the region –Second pass: regressions and rereading of the sentences after leaving region

67 F&C: Experiment 1 the influence of thematic information Reduced Reduced The evidence examined by the lawyer turned out to be unreliable. The evidence examined by the lawyer turned out to be unreliable. Unreduced Unreduced The evidence that was examined by the lawyer turned out to be unreliable. (C = Critical Region that disambiguates local ambiguity) C C C-1 C-2 C+1 C+2 C+1 C+2

68 F&C: Experiment 1 the influence of thematic information The evidence examined by the lawyer turned out to be unreliable. AnimInanim RR UR PREDICTIONS CONCERNING C & C+1 C C-1 C-2 C+1C+2AnimInanimRR UR MODULAR (GARDEN-PATH MODEL) INTERACTIVE FAST SLOW FAST SLOW FAST FAST OR SLOW PREDICTIONS

69 The evidence examined by the lawyer turned out to be unreliable. AnimInanim RR UR PREDICTIONS CONCERNING C & C+1 C C-1 C-2 C+1C+2AnimInanimRR UR MODULAR (GARDEN-PATH MODEL) INTERACTIVE FAST SLOW FAST SLOW FAST FAST OR SLOW PREDICTIONS Main Effect of Reduction Main Effect of Reduction (maybe) Main Effect of Animacy Interaction Effect of Animacy x Reduction NO Main Effect of Animacy

70 The evidence examined by the lawyer turned out to be unreliable. AnimInanim RR UR PREDICTIONS CONCERNING C & C+1 C C-1 C-2 C+1C+2AnimInanimRR UR MODULAR (GARDEN-PATH MODEL) INTERACTIVE FAST SLOW FAST SLOW FAST FAST OR SLOW PREDICTIONS Animate Reduced Animate Unreduced Inanimate Reduced Inanimate Unreduced SLOW FAST SLOW FAST SLOW FAST MODULAR INTERACTIVE

71 The evidence examined by the lawyer turned out to be unreliable. C C-1 C-2 C+1C+2 Animate Reduced Animate Unreduced Inanimate Reduced Inanimate Unreduced SLOW FAST SLOW FAST SLOW FAST MODULAR INTERACTIVE FAST OR SLOW PREDICTIONS ACTUAL RESULTS

72 Ferreira & Clifton (1986) Q: Is the initial syntactic processing stage influenced by: 1. thematic/semantic information (Exp. 1) 2. pragmatic or contextual information (Exp. 2 & 3) A: No, according to Garden-Path Model. Autonomous/modular parser. Context information is used only after initial parse. Goal of Experiments: To experimentally test (and provide evidence) for such a position.

73 F&C: Experiment 2 Referential Context Information Minimal(MA)Non-minimal(NMA) Supportive MA-MA NMA-NMA Neutral(N) N-MA N-NMA ATTACHMENT CONTEXT

74 F&C: Experiment 2 Referential Context Information What types of sentences were tested? What types of sentences were tested? –VP-Attached vs. NP-Attached –Main Clause vs. Reduced Relative Clause

75 VP- vs. NP-attachment Sam loaded the boxes on the cart / before his coffee break. Sam loaded the boxes on the cart / before his coffee break. Sam loaded the boxes on the cart / onto the van. Sam loaded the boxes on the cart / onto the van. VP-attached: NP-attached (VP-attachment: Minimal Attachment) (NP-attachment: Non-minimal Attachment)

76 VP- vs. NP-attachment Sam loaded the boxes on the cart / before lunch. (VP-attachment: Minimal Attachment) Sam loaded the boxes on the cart / before lunch. (VP-attachment: Minimal Attachment) Sam loaded the boxes on the cart / onto the van (NP-attachment: Non-minimal Attachment) Sam loaded the boxes on the cart / onto the van (NP-attachment: Non-minimal Attachment) VP-attached: MinimalNP-attached: Non-Minimal NP S VP NP V Sam the boxes PP loaded on the cart S VP NP V PP Sam the boxes loadedon the cart

77 F&C: Experiment 2 Referential Context Information Support + NMA Support + MA No Support + MA No Support + NMA

78 Main vs. Reduced Relative The man played the tape / and liked it. The man played the tape / and liked it. The man played the tape / liked it. The man played the tape / liked it. MAIN CLAUSEREDUCED RELATIVE CLAUSE (MAIN CLAUSE: Minimal Attachment) (REDUCED RELATIVE: Non-minimal Attachment)

79 Main vs. Reduced Relative The man played the tape / and liked it. (MAIN CLAUSE: Minimal Attachment) The man played the tape / and liked it. (MAIN CLAUSE: Minimal Attachment) The man played the tape / liked it. (REDUCED RELATIVE: Nonminimal Attachment) The man played the tape / liked it. (REDUCED RELATIVE: Nonminimal Attachment) NP VP S NP V The man played the tape MAIN CLAUSE: Minimal REDUCED RELATIVE CLAUSE: Non-Min. NP VP S NP V VP V The man played the tapeliked NP t S and CONJ

80 F&C: Experiment 2 Referential Context Information Support + NMA Support + MA No Support + MA No Support + NMA

81 MinNon-min Support Neutral F&C: Experiment 2 Referential Context Information MinNon-minSupport Neutral Fast/Slow PREDICTIONS FOR CRITICAL REGION C MODULAR (GARDEN-PATH MODEL) INTERACTIVE FAST SLOW FAST SLOW FAST est Effect of Attachment Effect of Attachment (maybe) Effect of Context Effect of Attachment x Context (maybe) NO Effect of Context

82 F&C: Experiment 2 Referential Context Information 1 st Pass 2 nd Pass Reading Time C-1C Sam loaded the box on the cart C-1C Sam loaded the box on the cart Results for VP-attached vs. NP-attached. NO Main Effect of Attachment Main Effect of Region Interaction Effect of Attachment x Region NO Main Effect of Context Main Effect of Attachment Main Effect of Region Interaction Effect of Attachm. x Region NO Main Effect of Context

83 F&C: Experiment 2 Referential Context Information Reading Time C-1C C+1 The editor played the tape (and) agreed the story was big C-1C C+1 The editor played the tape (and) agreed the story was big 1 st Pass 2 nd Pass Results for Main vs. Reduced Main Effect of Attachment Main Effect of Region NO Main Effect of Context Main Effect of Attachment Main Effect of Region Interaction Effect of Attachm. x Region NO Main Effect of Context

84 F&C: Experiment 2 Referential Context Information Main Effect of Attachment NO Main Effect of Context EASIEST HARDEST E.g. Did Sam play the tape? Eye-movement Back to Previous Region & Percentage Correct on Probe Qs Eye movements back

85 F&C: Experiment 3 Replication of Experiment 2 with another method Self Paced Reading Time Self Paced Reading Time –Dashed lines as place holders for letters –Button press to see regions Replacing dashed lines Replacing dashed lines

86

87

88 F&C: Experiment 3 Replication of Experiment 2 with another method

89 Main Effect of Attachment Main Effect of Region Interaction Effect of Attachment x Region Interaction Effect of Context x Attachment! (Context supporting minimal attachment reduced reading time. Context supporting non-minimal attachment increased reading time)

90 Ferreira & Clifton (1986) General Conclusions General Conclusions –Support Modular View Initial parse disregard Initial parse disregard –Thematic information –Referential context Support for Minimal Attachment Support for Minimal Attachment ANY CRITIQUES? ANY CRITIQUES?


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