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The Subject Gap Advantage in Georgian relative clause processing Steven Foley srfoley@ucsc.edu North East South Caucasian Chalk Circle (NESCCC) May 9, 2017 Introduction Relative clauses with subject gaps ( SRC s) are generally easier to

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The Subject Gap Advantage in Georgian relative clause processing

Steven Foley • srfoley@ucsc.edu North East South Caucasian Chalk Circle (NESCCC) May 9, 2017

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Introduction

Relative clauses with subject gaps (SRCs) are generally easier to process than ones with object-gaps (ORCs).

(1) the painter [RC who __ inspired the writer ] SRC (2) the painter [RC whom the writer inspired __ ] ORC Evidence: acquisition, aphasia, ERPs, reading times, eye movements, comprehension, acceptability, disambiguation bias

(see Gibson 1998, Kwon et al 2010 for reviews). 1

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Introduction

What might explain this Subject Gap Advantage (SGA)?

  • Hierarchical structure?
  • Incremental cues from morphological case?
  • Linear/temporal distance?

2

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Introduction

RC-processing data has primarily come from NOM–ACC languages with postnominal RCs (cf. Anand et al 2011).

T ypological confound: the three hypotheses converge given a language with these properties.

Enter Georgian , a split-ergative language with pre- and post-nominal RCs.

A perfect storm for disentangling SGA theories!

3

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Present study

T wo self-paced reading experiments

  • Experiment 1: Case alignment pattern

NOM–ACC vs. ERG–ABS vs. DAT–ABS

  • Experiment 2: Relative clause position

N [RC … ] vs. [RC … ] N

4

⎛ ⎞ ⎜ ⎟ ⎝ ⎠

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Present study

Both experiments provide strong evidence for a Structural source of the SGA.

  • Reading times (RT

s) slowed where an ORC parse becomes unambiguous, no matter the case alignment.

Disambiguation effect

  • RT

s slowed again at the RC-final Verb.

Integration effect (cf. Staub 2010, Levy & Keller 2013).

5

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Roadmap

  • Theories of the SGA
  • Morphosyntactic properties of Georgian
  • Experimental design
  • Predictions
  • Results & Discussion

6

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Roadmap

  • Theories of the SGA
  • Hierarchical structure: Subjects are universally more accessible
  • Morphological cues: NOM & ABS DPs are least surprising/informative

7

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The Subject Gap Advantage

Structural Hypothesis (Keenan & Comrie 1977)

  • Universally, subjects are higher (→ more accessible)

than objects.

(3) the painter [RC who [TP __ inspired the writer ]] SRC 😈 (4) the painter [RC whom the writer [VP inspired __ ]] ORC 💪

8

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The Subject Gap Advantage

Structural Hypothesis (Keenan & Comrie 1977)

  • Prediction: SGA, no matter a language’s case alignment

(Ch’ol & Q’anjob’al: Clemens et al. 2015, Avar: Polinsky et al. 2012).

(5) the painter [RC whoERG [TP __ inspired the writer ]] SRC 😈 (6) the painter [RC whoABS the writer [VP inspired __ ]] ORC 💪

9

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The Subject Gap Advantage

Case Cue Hypothesis (Polinsky et al. 2012; cf. Hale 2006)

  • Information from a dependent case (ACC in English) causes

a processing cost.

(7) the painter [RC whoNOM __ inspired the writer ] SRC 💂 (8) the painter [RC whomACC the writer inspired __ ] ORC 🤕

10

Must be transitive!

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The Subject Gap Advantage

Case Cue Hypothesis (Polinsky et al. 2012; cf. Hale 2006)

  • Prediction: ERG–ABS languages will have an Object Gap

Advantage (OGA)! (Basque: Carreiras et al. 2010; Avar: Polinsky et al. 2012).

(9) the painter [RC whoERG __ inspired the writer ] SRC 🤕 (10) the painter [RC whoABS the writer inspired __ ] ORC 💂

11

Must be transitive!

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Summary

Theories of the SGA are difficult to disentangle — unless you’re in an ergative language.

NOM–ACC ERG–ABS Structure SGA SGA Case Cue OGA

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Roadmap

  • Theories of the SGA
  • Morphosyntactic properties of Georgian
  • Split ergativity

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Georgian 101: Split ergativity

Case on subjects & objects depends on the tense–aspect–mood / TAM (Aronson 1995).

(11) ekim-i ḳar-s gaaġebs doctor-NOM door-DAT

  • pen.TR.FUT

‘the doctor will open the door’ (12) ḳar-i gaiġeba door-NOM open.INTR.FUT ‘the door will open’

14

TR SUBJ INTR SUBJ TR OBJ

Alignment

FUT NOM DAT

NOM–ACC

PAST PERF

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Georgian 101: Split ergativity

Case on subjects & objects depends on the tense–aspect–mood / TAM (Aronson 1995).

(13) ekim-ma ḳar-i gaaġo doctor-ERG door-NOM open.TR.PAST ‘the doctor opened the door’ (14) ḳar-i gaiġo door-NOM open.INTR.PAST ‘the door opened’

15

TR SUBJ INTR SUBJ TR OBJ

Alignment

FUT NOM DAT

NOM–ACC

PAST ERG NOM

ERG–ABS

PERF

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Georgian 101: Split ergativity

Case on subjects & objects depends on the tense–aspect–mood / TAM (Aronson 1995).

(15) ekim-s ḳar-i gauġia doctor-DAT door-NOM open.TR.PERF ‘the doctor has opened the door’ (16) ḳar-i gaġebula door-NOM open.INTR.PERF ‘the door has opened’

16

TR SUBJ INTR SUBJ TR OBJ

Alignment

FUT NOM DAT

NOM–ACC

PAST ERG NOM

ERG–ABS

PERF DAT NOM

DAT–ABS

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Recap

RC processing has been investigated in only a few (Split-)Ergative languages. But these are just the place to test theories of the

  • SGA. For Georgian…
  • Dependent case may be on Subj (ERG) or Obj (DAT).

Case Hypothesis: SGA if FUT (NOM–ACC); OGA if PAST or PERF (ERG–ABS or DAT–ABS)

17

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Recap

RC processing has been investigated in only a few (Split-)Ergative languages. But these are just the place to test theories of the

  • SGA. For Georgian…
  • Dependent case may be on Subj (ERG) or Obj (DAT).

Structural Hypothesis: SGA in all TAMs

18

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Roadmap

  • Theories of the SGA
  • Morphosyntactic properties of Georgian
  • Experimental design
  • Overview of Experiment 1
  • Item Sets

19

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Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

20

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Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

21

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Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

22

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Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

23

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Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

24

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SLIDE 26

Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

25

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Design Overview

T ask: Self-paced reading

A technique for measuring incremental processing.

Design: 3 (TAM/alignment) × 2 (gap site)

{FUT, PAST, PERF} × {SRC, ORC} 36 item sets, 64 fillers (including 24 items of Experiment 2) Each sentence followed by a Y–N comprehension Q

26

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Design Overview

Participants: 57 native Georgian speakers

46 ♀ / 11 ♂, average age 23, paid 40 lari All in Tbilisi , recruited via Facebook 4 excluded from analysis for low comprehension scores

Conducted online via Ibex (Drummond 2007)

Georgian script, Georgian instructions

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Item Sets

Item set: {FUT, PAST, PERF} × {SRC, ORC}

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HdN

W2

whP

W3

XP1

W4

XP2

W5

Adj

W6

CoArg

W7

V

W8

(17) … gogo, … girl.NOM ⎡ romel-ic ⎣RC which-NOM bnel dark ṭq̇e-ši woods-in maġal-∅ tall-DAT bič̣-s boy-DAT naxavs ⎤ … see.FUT ⎦ ‘…the girl [RC who __ will see the tall boy in the dark woods ]…’ (18) … gogo, … girl.NOM ⎡ romel-sac ⎣RC which-DAT bnel dark ṭq̇e-ši woods-in maġal-i tall-NOM bič̣-i boy-NOM naxavs ⎤ … see.FUT ⎦ ‘…the girl [RC who the tall boy will see __ in the dark woods ]…’

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Item Sets

Item set: {FUT, PAST, PERF} × {SRC, ORC}

29

HdN

W2

whP

W3

XP1

W4

XP2

W5

Adj

W6

CoArg

W7

V

W8

(17) … gogo, … girl.NOM ⎡ romel-ic ⎣RC which-NOM bnel dark ṭq̇e-ši woods-in maġal-∅ tall-DAT bič̣-s boy-DAT naxavs ⎤ … see.FUT ⎦ ‘…the girl [RC who __ will see the tall boy in the dark woods ]…’ (18) … gogo, … girl.NOM ⎡ romel-sac ⎣RC which-DAT bnel dark ṭq̇e-ši woods-in maġal-i tall-NOM bič̣-i boy-NOM naxavs ⎤ … see.FUT ⎦ ‘…the girl [RC who the tall boy will see __ in the dark woods ]…’

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Item Sets

Item set: {FUT, PAST, PERF} × {SRC, ORC}

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HdN

W2

whP

W3

XP1

W4

XP2

W5

Adj

W6

CoArg

W7

V

W8

(19) … gogo, … girl.NOM ⎡ romel-mac ⎣RC which-ERG bnel dark ṭq̇e-ši woods-in maġal-i tall-NOM bič̣-i boy-NOM naxa ⎤ … see.PAST ⎦ ‘…the girl [RC who __ saw the tall boy in the dark woods ]…’ (20) … gogo, … girl.NOM ⎡ romel-ic ⎣RC which-NOM bnel dark ṭq̇e-ši woods-in maġal-ma tall-ERG bič̣-ma boy-ERG naxa ⎤ … see.PAST ⎦ ‘…the girl [RC who the tall boy saw __ in the dark woods ]…’

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Item Sets

Item set: {FUT, PAST, PERF} × {SRC, ORC}

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HdN

W2

whP

W3

XP1

W4

XP2

W5

Adj

W6

CoArg

W7

V

W8

(19) … gogo, … girl.NOM ⎡ romel-mac ⎣RC which-ERG bnel dark ṭq̇e-ši woods-in maġal-i tall-NOM bič̣-i boy-NOM naxa ⎤ … see.PAST ⎦ ‘…the girl [RC who __ saw the tall boy in the dark woods ]…’ (20) … gogo, … girl.NOM ⎡ romel-ic ⎣RC which-NOM bnel dark ṭq̇e-ši woods-in maġal-ma tall-ERG bič̣-ma boy-ERG naxa ⎤ … see.PAST ⎦ ‘…the girl [RC who the tall boy saw __ in the dark woods ]…’

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Item Sets

Item set: {PAST, FUT, PERF} × {SRC, ORC}

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HdN

W2

whP

W3

XP1

W4

XP2

W5

Adj

W6

CoArg

W7

V

W8

(21) … gogo, … girl.NOM ⎡ romel-sac ⎣RC which-DAT bnel dark ṭq̇e-ši woods-in maġal-i tall-NOM bič̣-i boy-NOM unaxavs ⎤ … see.PERF ⎦ ‘…the girl [RC who __ has seen the tall boy in the dark woods ]…’ (22) … gogo, … girl.NOM ⎡ romel-ic ⎣RC which-NOM bnel dark ṭq̇e-ši woods-in maġal-∅ tall-DAT bič̣-s boy-DAT unaxavs ⎤ … see.PERF ⎦ ‘…the girl [RC who the tall boy has seen __ in the dark woods ]…’

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Item Sets

Item set: {PAST, FUT, PERF} × {SRC, ORC}

33

HdN

W2

whP

W3

XP1

W4

XP2

W5

Adj

W6

CoArg

W7

V

W8

(21) … gogo, … girl.NOM ⎡ romel-sac ⎣RC which-DAT bnel dark ṭq̇e-ši woods-in maġal-i tall-NOM bič̣-i boy-NOM unaxavs ⎤ … see.PERF ⎦ ‘…the girl [RC who __ has seen the tall boy in the dark woods ]…’ (22) … gogo, … girl.NOM ⎡ romel-ic ⎣RC which-NOM bnel dark ṭq̇e-ši woods-in maġal-∅ tall-DAT bič̣-s boy-DAT unaxavs ⎤ … see.PERF ⎦ ‘…the girl [RC who the tall boy has seen __ in the dark woods ]…’

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Roadmap

  • Theories of the SGA
  • Morphosyntactic properties of Georgian
  • Experimental design
  • Predictions

34

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Consequences of Split Ergativity

Some cases are more informative than others.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

35

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Consequences of Split Ergativity

Some cases are more informative than others.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

36

SRC!

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Consequences of Split Ergativity

Some cases are more informative than others.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

37

ORC! SRC!

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Consequences of Split Ergativity

Some cases are more informative than others.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

38

ORC! SRC! ORC! SRC!

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Consequences of Split Ergativity

Some cases are more informative than others.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

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ORC! SRC! ORC! SRC! ORC! SRC!

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Predictions: Structural Theory

Slower RTs︎ at an unambiguous ORC cue.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

40

ORC! 💪 SRC! 😈 ORC! 💪 SRC! 😈 ORC! 💪 SRC! 😈

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Predictions: Case Theory

Slower RTs︎ at DP bearing dependent case.

HeadN whP-ERG

Filler XP

CoArg-NOM V-PAST CoArg-ERG V-PAST whP-NOM CoArg-DAT V-FUT V-PERF whP-DAT CoA-NOM V-FUT V-PERF

41

🤕 💂 💂 💂 🤕 🤕 🤕

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Predictions: Summary

Three critical regions to look out for.

whP CoArg Verb

Structure

ALL: 😈

(Any case could be a subject)

ERG: 💪 NOM/DAT: 😈

(ERG is an unambiguous ORC cue)

FUT/PERF ORC: 💪 ELSE: 😈

(TAM disambiguates gap site)

Case

NOM: 💂 ERG/DAT: 🤕

(Dependent cases cause a slowdown)

NOM: 💂 ERG/DAT: 🤕

(Dependent cases cause a slowdown)

ALL: 💂

(Transitive Structure has already been disambiguated)

42

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Roadmap

  • Theories of the SGA
  • Morphosyntactic properties of Georgian
  • Experimental design
  • Predictions
  • Results & Discussion

43

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Results

RT differences (ORC − SRC) by region: PAST (ERG–ABS)

44

ORC is slower SRC is slower ORC: HdN ⎡ whP XP1 XP2 Adj CoArg V.PAST ⎤ ⎣RC NOM

ERG ERG

⎦ SRC: HdN ⎡ whP XP1 XP2 Adj CoArg V.PAST ⎤ ⎣RC ERG

NOM NOM

⎦

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Results

RT differences (ORC − SRC) by region: PERF (DAT–ABS)

45

ORC is slower SRC is slower ORC: HdN ⎡ whP XP1 XP2 Adj CoArg V.PERF ⎤ ⎣RC NOM

DAT DAT

⎦ SRC: HdN ⎡ whP XP1 XP2 Adj CoArg V.PERF ⎤ ⎣RC

DAT NOM NOM

⎦

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Results

RT differences (ORC − SRC) by region: FUT (NOM–ACC)

46

ORC is slower SRC is slower ORC: HdN ⎡ whP XP1 XP2 Adj CoArg V.FUT ⎤ ⎣RC

DAT NOM NOM

⎦ SRC: HdN ⎡ whP XP1 XP2 Adj CoArg V.FUT ⎤ ⎣RC NOM

DAT DAT

⎦

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Summary of results

Structural Theory’s predictions were borne out. Disambiguation Integration Effect Effect

47

whP CoArg Verb

Structure

No difference

(Any case could be a subject in principle)

ERG: 💪 NOM/DAT: 😈

(ERG is an unambiguous ORC cue)

ALL ORCS: 💪 ALL SRCS: 😈

(SGA shows up again at the verb)

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Conclusion

Georgian’s unique grammatical properties allow it to distinguish multiple theories of the SGA.

48

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Conclusion

Despite Split Ergativity, SPR data show a clear SGA. RTs increase when…

an ORC parse is disambiguated. argument structure is integrated at the verb.

49

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SLIDE 51

Conclusion

Evidence for the Structural Hypothesis: Subject Gaps are easiest 😈 since they’re most accessible in the phrase structure.

50

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Conclusion

Directions for future research

  • Just why are subjects special?

Is it really phrase structure? Or maybe frequency?

  • Look beyond Subject vs. Object gaps

Direct vs. Indirect Object, Argument vs. Adjunct

51

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Acknowledgements

In the US  Matt Wagers, Sandy Chung, Ivy Sichel, Masha Polinsky, Chelsea Miller, the 290 Crew In Georgia  Irma Miminoshvili, Natia Botkoveli, Mariam Navadze, Salome Kobalia

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References

Aronson, Howard I. (1995). Georgian: A reading grammar. Columbus, Ohio: Slavica. Carreiras, Manuel, Jon Andoni Duñabeitia, Marta Vergara, Irene de la Cruz-Pavía, and Itziar Laka (2010). Subject relative clauses are not universally easier to process: Evidence from Basque. Cognition 115: 79–92. Clemens, Lauren Eby, Jessica Coon, Pedro Mateo Pedro, Adam Milton Morgan, Maria Polinsky, Gabrielle T andet, and Matthew Wagers (2015). Ergativity and the complexity of extraction: a view from Mayan. Natural Language and Linguistic Theory 33: 417–467. Drummond, A. 2007. Ibex Farm. Experiment software. <http://spellout.net/ibexfarm>. Gibson, Edward (1998). Linguistic complexity: Locality of syntactic dependencies. Cognition 68: 1–76. Levy, R. P ., & Keller, F . (2013). Expectation and locality effects in German verb-final structures. Journal of Memory and Language, 68(2). Keenan, E., & B. Comrie. 1977. Noun phrase accessibility and universal grammar. Linguistic Inquiry 8: 63–99. Kwon, Nayoung, Yoonhyoung Lee, Peter C. Gordon, Robert Kluender, and Maria Polinsky (2010). Cognitive and linguistic factors affecting subject/object asymmetry: An eye-tracking study of pre-nominal relative clauses in Korean. Language 86: 546–582. Lin, Yowyu, and Susan M. Garnsey (2007). Plausibility and the resolution of temporary ambiguity in relative clause comprehension in Mandarin. Poster presented at the 20th annual CUNY Conference on Human Sentence Processing, University of California, San Diego. Polinsky, Maria, Carlos Gómez Gallo, Peter Graff, and Ekaterina Kravtchenko (2012). Subject preference and ergativity. Lingua 122: 267–277. Staub, A. (2010). Eye movements and processing difficulty in object relative clauses. Cognition 116. Traxler, M., et al. 2002. Processing subject and object relative clauses: Evidence from eye movements. Journal of Memory and Language 47. Ueno, Mieko, and Susan M. Garnsey (2008). An ERP study of the processing of subject and object relative clauses in

  • Japanese. Language and Cognitive Processes 23.646–88.

Vasishth, S., et al. 2013. Processing Chinese relative clauses: Evidence for the Subject-Relative Advantage. PLoS ONE 8(10): e77006.

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დიდი მადლობა თქვენი ყურადღებისთვის!

Thanks for listening!

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Linearity & RC Processing

Distance Hypothesis (Gibson 1998, Lewis & Vasishth 2005)

  • If N [RC …] (as in English), the filler (head noun or relative pronoun)

is closer to the gap in an SRC.

(23) the painter [RC who __ inspired the writer ] SRC 😅 (24) the painter [RC whom the writer inspired __ ] ORC 😬

55

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Linearity & RC Processing

Distance Hypothesis (Gibson 1998, Lewis & Vasishth 2005)

  • Prediction: If [RC … ] N, there should be no SGA — maybe

even an OGA (cf. Chinese: Gibson & Kuo 2010).

(25) [RC who __ inspired the writer ] the painter SRC 😬 (26) [RC whom the writer inspired __ ] the painter ORC 😅

56

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Experiment 2: RC Position

Design: 2 { N [RC … ], [RC … ] N } × 2 {SRC, ORC} (all in PAST)

(27) a. is gogo, ⎡ bič̣-i/ma rom bnel ṭq̇e-ši naxa, ⎤ …

DEM girl.NOM ⎣RC boy-NOM/ERG C0

dark woods-in see.PAST ⎦ ‘that girl [RC that {__ saw} the boy {saw __} in the dark woods] …’

  • b. ⎡

bič̣-i/ma rom bnel ṭq̇e-ši naxa, ⎤ is gogo … ⎣RC boy-NOM/ERG C0 dark woods-in see.PAST ⎦

DEM

girl.NOM ‘that girl [RC that {__ saw} the boy {saw __} in the dark woods] …’

57

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SLIDE 59

Experiment 2: Results

RT differences (ORC − SRC) by region: N [RC … ]

58

ORC is slower SRC is slower ORC: HdN ⎡ CoArg XP1 XP2 V.PAST ⎤ ⎣RC

ERG

⎦ SRC: HdN ⎡ CoArg XP1 XP2 V.PAST ⎤ ⎣RC

NOM

⎦

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SLIDE 60

Experiment 2: Results

RT differences (ORC − SRC) by region: N [RC … ]

59

ORC is slower SRC is slower ORC: ⎡ CoArg XP1 XP2 V.PAST ⎤ HdN ⎣RC

ERG

⎦ SRC: ⎡ CoArg XP1 XP2 V.PAST ⎤ HdN ⎣RC NOM ⎦