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A usage-based account of subextraction effects

  • Rui P. Chaves EMAIL logo and Adriana King
From the journal Cognitive Linguistics

Abstract

The idea that conventionalized general knowledge – sometimes referred to as a frame – guides the perception and interpretation of the world around us has long permeated various branches of cognitive science, including psychology, linguistics, and artificial intelligence. In this paper we provide experimental evidence suggesting that frames also play a role in explaining certain long-distance dependency phenomena, as originally proposed by Deane (1991). We focus on a constraint that restricts the extraction of an NP from another NP, called subextraction, which Deane (1991) claims is ultimately a framing effect. In Experiment 1 we provide evidence showing that referents are extractable to the degree that they are deemed important for the proposition expressed by the utterance. This suggests that the world knowledge that the main verb evokes plays a key role in establishing which referents are extractable. In Experiment 2 we offer evidence suggesting that the acceptability of deep subextractions is correlated with the overall plausibility of the proposition, suggesting that complex structures can evoke complex frames as well, if sufficiently frequent and semantically coherent, and therefore more easily license deeper subextractions.

Acknowledgements

We wish to thank the Editors John Newman and Dagmar Divjak, and the anonymous reviewers for their invaluable assistance and feedback. We also wish to thank the Department of Linguistics at the University at Buffalo for an internal research grant that supported the experimental component of this research.

Appendix

A

Below are the items used in the acceptability experiment reported in Section 3.1. The verb that appears immediately to the left of ‘/’ causes the extracted element to be more topical for the proposition, and the verb that appears immediately after ‘/’ causes the extracted element to be less topical. The norming (declarative) experimental items were systematically constructed from those below. Each item is followed by the respective COCA frequency counts. For example, the verb like (however inflected) is followed by the complement story or stories (with at most one work in between) 462 times; see footnote 9 above for more details. Add-one Smoothing of the raw counts to avoid zeros had no quantitative or qualitative impact on the statistical results.

  1. What did Mary like / proof-read a story about?   (462/0)

  2. What did John direct / narrate a documentary about?   (34/14)

  3. What did Bill create / find a powerpoint about?   (0/0)

  4. What did Kate give / reschedule a presentation about?   (182/0)

  5. What did Sarah start / transcribe a conversation about?   (364/5)

  6. What did Steve ask / hear a question about?   (9066/350)

  7. What did Scott discuss / mistype a report about?   (29/0)

  8. What did Katherine file / overlook a complaint about?   (750/0)

  9. What did Brian criticize / rip a pamphlet about?   (0/0)

  10. What did Chris make / ruin a joke about?   (847/3)

  11. What did Melissa rent / rewind a movie about?   (73/3)

  12. What did Rich write / see a book about?   (6228/296)

  13. What did Isabella buy / misplace a magazine about?   (94/0)

  14. What did Frank draft / xerox a movie script about?   (10/1)

  15. What did Kim teach / miss a class about?   (702/75)

  16. What did Leo read / discard a novel about?   (372/0)

  17. What did Nate prepare / hear a speech about?   (43/138)

  18. What did Kayla post / misread a comment about?   (484/0)

  19. What did Peter create / postpone a workshop about?   (7/0)

  20. What did Caitlin take / return a quiz about?   (11/0)

Appendix B

Below are the items used in the two acceptability experiments reported in Section 3.2. The norming (declarative) experimental counterparts were systematically constructed from the items listed below. No verb-noun-noun frequencies were included in the analysis because their occurrence is too sparse to appear even in large corpora like COCA.

  1. Which President did pundits create blogs about the impeachment of?

  2. Which actress did students write a paper about the photos of?

  3. Which article did the publisher change the font in the title of?

  4. Which artist did the kids hear stories about pictures of?

  5. Which bridge did the Governor order a study about the condition of?

  6. Which committee was the Mayor offered an appointment to the chairmanship of?

  7. Which company did lobbyists advise the chairman of the board of?

  8. Which content does the editor have strict control over the publication of?

  9. Which disaster did the church help families of the victims of?

  10. Which historical figure did visitors take photos of the statue of?

  11. Which institution did researchers write a paper about the history of?

  12. Which official did the Senate lack votes for the impeachment of?

  13. Which pesticide did farmers question the analysis of the impact of?

  14. Which reporter did the lawyers revise the wording of the email to?

  15. Which suspect did the witness see enemies of friends of?

  16. Which topic did the experts receive requests for articles about?

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Received: 2018-11-01
Revised: 2019-04-02
Accepted: 2019-04-13
Published Online: 2019-09-03
Published in Print: 2019-11-26

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