The Interaction of Lexical and Syntactic Ambiguity

1. The Interaction of Lexical and Syntactic Ambiguity by Maryellen C. MacDonald presented by Joshua Johanson

2. What do you mean by lexical and syntactic ambiguity? • Lexical Ambiguity • financial bank/river bank • Syntactic Ambiguity • I saw the spy with the binoculars • Lexical and Syntactic Ambiguity • to watch/a watch

3. Approach 1: Unified Approach • Both syntax and lexical ambiguities resolved via probabilistic constraints • Very complex interaction • All lexical and syntactic interpretations are activated until one is favored • The alternative view uses garden sentences to argue that only one syntactic interpretation is activated • I told the girl that the boy met the story • While Mary was mending the sock fell on the floor

4. Approach 2: Different mechanism for each type of ambiguity • Lexical Ambiguity • Representations are created and stored • All senses are activated in parallel until most probable one is chosen • Sytactic Ambiguity • Parses are constructed, not stored • There is only one serial parse • Lexical and Semantic Ambiguity • The Delay Model

5. Delay Model • If there is an interaction between lexical and syntactic ambiguity, resolution of the ambiguity waits until it is no longer ambiguous • I know that the desert trains could resupply the camp. • I know that the desert trains soldiers to be tough

6. Frazier and Rayner’s experiment • Measured eye fixation for reading times • Compared ambiguous readings with unambiguous readings • Used this/these to disambiguate • This desert trains • These desert trains

7. Results

8. Criticism • End region is not consistent (3-10 words) • Delay may come from another source besides the ambiguity • ‘This’ and ‘These’ are usually used as anaphoric references, but there is no mention of which desert or which trains these refer to. • This could be awkward and may be the cause in the delay, not the disambiguation

9. MacDonald’s Experiment • 53 MIT undergraduates tested • Saw one word at a time on the screen • Pressed space when they were done • Asked comprehension question at the end (No feedback) • Threw out tests if the comprehension question were wrong • Threw out 5 participants who got more than 20% of the comprehension questions wrong

10. Sentences • Modified Frazier’s questions to have exactly four words after the ambiguous phrase • Instead of using the modifier to dis-ambiguate, they used the part of speech • “the deserted trains” • “the desert trained” • Kept the this/these distinction

11. Sample Question Set

12. Results from Ambiguous Region • No difference between “the desert trains” and “the deserted trains” • Using anaphoric modifiers increases reading time across the board • Disambiguation increases reading time in the NV interpretation

13. Why does disambiguation increase reading time • Inherent NN bias affected the reading times • Readers might have confused “desert trained”, which is NV, with “desert-trained” which is an adjective • “The desert trains soldiers” doesn’t necessarily imply NV • “The desert trains (that) soldiers attacked were destroyed”

14. Results from the End Region • Obvious benefits from disambiguating “the” • Still some residual ‘this/these’ confusion, except when it disambiguates “these desert trains”

15. Experiment 2 • Hypothesis: A strong semantic bias affects ambiguity resolution • This would disprove the delay model, which suggests all disambiguation waits until the disambiguation is resolved. • Avoids anaphoric determiners • “corporation fires” (ambiguous) • “corporations fire” (unambiguous)

16. Setup • 44 (out of 46) MIT undergrads • Same basic setup as before with keyboard and comprehension questions • 16 questions, each with and without and ambiguity with and without supportive bias • Uses different NV combinations to bias the interpretation • “corporation fires” NV bias • “warehouse fires” NN bias

18. Results

19. Observations • Very little difference in the Supportive Bias times • Still seems to be a “reverse ambiguity” effects • There might be something to do with it taking longer to process NVs that NNs. • Using a word that is still ambiguous but has a stronger bias affects the results • This is not supported by the delay model

20. Can we predict how strong the effect will be? • How often is the word the head of the phrase rather than the modifier • How often is the word a verb rather than a noun (‘to warehouse prisoners’) • How often do the words appear together • How plausible is the situation (Is a corporation more likely to have a fire or a warehouse?)

21. How they collected it • Wall Street Journal corpus (yea!!!) • Counted the number occurrences for the ‘how often’ questions. • Plausibility is subjective, and could be influenced by other factors • They tested 96 native English speakers on sentence completion and counted number of times they completed it as a NN vs. NV • “The warehouse fires…”

22. Results • Percentage Heads: • Supportive bias (corporation fires) – 85.5% • Unsupportive bias (warehouse fires) – 58.8% • Noun/Verb interpretation • 6.5% verb usage (to warehouse prisoners) • Co-occurrence • Supportive bias .1% • Unsupportive bias 2.1%(exact) and 42.%(combined) • Still very sparse, went with a Boolean exist or not exist • Sentence Completion Norms • Supportive bias – 50.9% NV interpretation • Unsupportive bias – 9.6% NV interpretation

23. How do these biases affect reading times? • Stepwise regression function • Stepwise regression only used the head measure results: • r2 = .19, F(1,30), p =.01 • Simple regression • As supportiveness for NV interpretation increase, reading time increases • Co-occurrence had the reverse effect, since co-occurrence seems to promote NN interpretation

24. Do these affect unambiguous sentences • Yes. People tend to read plausible sentences more quickly than less plausible sentences. This may indicate that plausibility might help disambiguate more than modifiers. • “the corporations fire” was read more quickly than “the warehouses fire”.

25. Let’s do another step-wise regression! • This time we use the difference between the ambiguous and unambiguous readings • The partial correlation between reading time differences and the percentage head measure was .47 • If the word is more likely to be a head, the reading time increased with the ambiguity. • The partial correlation with the sentence completion norms was -.37 • If the word is more plausible, the reading time decreases with the ambiguity

26. Shouldn’t it be the other way around? • Apparently not. We know that NVs take longer to read than NNs. Maybe an incorrect reading of the word as a NN actually decreases the reading time more than having the correct reading of a NV. • “the warehouse fires…” • “the warehouses fire…”

27. I wonder how that affect carries out to the rest of the sentence?

29. Conclusions • Both lexical and combinatorial factors influence the ambiguity resolution process • These factors accounted for a significant portion of variance in reading times • More constraints promoted NV, the smaller the effect of ambiguity • This data does not support the delay model • Psycholinguistics has underestimated the influence of probabilistic information

30. Do we really keep track of the number of times that a noun is used as the head of a noun phrase? • We might need it to disambiguate between head nouns and noun modifiers • Maybe it just reflects other factors • Animacy? • Morphological analysis

31. Questions?