J Psycholinguist Res (2017) 46:827–845
DOI 10.1007/s10936-016-9461-z

Disambiguation and Integration in Korean Relative
Clause Processing
Michael Mansbridge1 · Sunju Park1 ·Katsuo Tamaoka1,2

Published online: 10 December 2016
© Springer Science+Business Media New York 2016

Abstract Previous studies on Korean relative clauses (RC) show that, with respect to processing, object-extracted relative clauses (ORC) are more difficult to process at the head noun
than subject-extracted relative clauses within temporarily ambiguous contexts. ORCs, however, are predicted by experience-based processing models to incur a greater processing cost
during early processing stages at the RC verb, since it is a likely locus of disambiguation
for RCs in Korean, and because ORCs are a less frequent structure. Consequently, the current study investigates whether processing difficulty for ORCs manifests itself at the RCverb using eye-tracking methods, a simple sentence structure and a sentential-decision task.
The results revealed significantly increased go-past reading times for ORCs at the RC verb.
We believe this is a result of a less frequent structure being more difficult to parse during
disambiguation. Accordingly, experience-based models of processing can accurately predictdifficulty for ORCs in Korean.
Keywords Korean · Relative clauses · Eye-tracking · Experience · Ambiguity

Introduction
Relative clauses (RC) are a prominently discussed topic in the field of experimental linguistics. Crosslinguistic research has shown that among the large majority of languages whichallow both subject-extracted relative clauses (SRC) and object-extracted relative clauses(ORCs), ORCs are both less frequent in corpora and more difficult to process and comprehend. Korean is an example of a language with this footprint. This has been demonstrated by
Kwon et al. (Kwon 2008; Kwon et al. 2010, 2013, 2006) using self-paced reading (SPR),

B Katsuo Tamaoka

ktamaoka@lang.nagoya-u.ac.jp

1

Department of Languages and Cultures, Nagoya University, Nagoya, Japan

2

Graduate School of Languages and Cultures, Nagoya University, Furo-cho, Chikusa-ku, Nagoya-shi,
Aichi-ken 466-8601, Japan

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eye-tracking and event related potentials (ERP). However, even within Korean, there havebeen numerous explanations to account for the difficulty of ORC processing. The aim of thecurrent study is to, after replicating the previous findings (i.e., ORC difficulty), use an eyetracking experiment to tease apart the factors that contribute to the ORC processing difficultyfound in Korean.

Korean Relative Clauses
In Korean, the RC precedes the head noun it modifies (i.e., RCs are head-final or prenominal). According to the World Atlas of Language Structures (Dryer 2013), languages withprenominal RCs are the second most frequent RC-ordering type (17%) after languages where
the RC follows the head noun (i.e., head-initial or post-nominal languages, such as English;70%). Examples of Korean head-final relative clauses are given below:
SRC: Opi [GAPi Uywon-ul
Op [gap

Kongyekha-n] Gijaneuni-i

Jinju-lul Boass-ta

senator-ACC attack-ADN] reporter-NOM Jinju-ACC

saw

English: The reporteri [whoi GAPi attacked the senator] saw Jinju.

ORC: Opi [Uywon-i

GAPi Kongyekha-n] Gijaneuni-i

Op [senator-NOM gap

Jinju-lul

attack-ADN] reporter-NOM Jinju-ACC

Boass-tasaw

English: The reporteri [whoi the senator attacked GAPi] saw Jinju.

Korean is a canonically SOV ordered language. As seen above, Korean RCs also demonstrate a canonical SOV word order. Additionally the only surface difference between the RC
structures is the case marker suffixed to the RC noun (e.g., senator-ACC & senator-NOM). In
both types of RCs, the RC is only overtly marked as a general embedded clause by the adnominal marker affixed to the embedded RC verb (e.g., attack-ADN). These features potentiallymake the RCs temporarily ambiguous during processing, since they lack an overt RC marker
at the left boundary of the clause. This is particularly true since Korean also allows bothpro-dropping and scrambling. In other words, without any facilitating discourse that could
signal an initial RC interpretation, the parser might misconstrue an RC as a matrix clause
until disambiguating information arrives. The phenomenon of clause type ambiguity is alsopresent in other prenominal languages and is addressed prominently in RC studies dealing
with Japanese (Miyamoto and Nakamura 2003; Ueno and Garnsey 2008) and Mandarin(Hsiao and Gibson 2003).
Kwon et al. (Kwon 2008; Kwon et al. 2010, 2013, 2006) have revealed much about theprocessing of Korean, and chiefly attribute the processing difficulty associated with ORCs toexperience-based (i.e., expectation-based) effects (Hale 2001, 2006; Levy 2008; MacDonald and Christiansen 2002; Mitchell et al. 1995) and structural-phrase integration (O’Grady
1997) at the head noun. While Kwon et al. (2010) illustrates that the locus of disambiguation for each clause may vary in temporarily ambiguous contexts and that the head noun
will guarantee a correct RC interpretation, the adnominal marker can at the very least disambiguate RCs from matrix clauses since matrix verbs lack adnominal markers. A brief
review of both processing accounts is given below, followed by a review of Kwon et al.’sfindings.

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Experience-Based Models
Experience-based models of processing (Hale 2001, 2006; Levy 2008; MacDonald andChristiansen 2002; Mitchell et al. 1995), regard processing to be guided by our prior experience with a given language. Accordingly, a more frequent structure in a language will
be easier to parse than a less frequent structure (see Demberg and Keller 2008; Husain
et al. 2014; Levy et al. 2013; Reali and Christiansen 2007). Since Korean ORCs occur lessfrequently in corpora than their SRC counterparts (Kwon 2008), experience-based models
predict that there should be greater difficulty when reading a Korean sentence containing
an ORC compared to a SRC. For temporarily ambiguous structures, such effects based on
the frequency of RC structures should not begin until the structure has been disambiguated.
At this point the expectation that the RC is a more frequent SRC would be met, or there
would be a dashed expectation if it is instead the less frequent ORC (Hale 2001, 2006; Levy
2008).
Evidence supporting an experience-based account for RC processing has already been
revealed for Mandarin Chinese. Mandarin is another language which has prenominal, temporarily ambiguous RC structures, and in which ORCs occur less frequently than SRCs.
What is more, Mandarin, similar to Korean, has a relativizer marker adjacent to the headnoun. In an ambiguous context, this relativizer would be the locus of disambiguation forclause type. Studies by Lin and Bever (2006) and Qiao et al. (2012) found an increased
processing cost at the relativizer position for ORCs within ambiguous contexts supporting
experience-based predictions. Furthermore, Jäger et al. (2015) demonstrated that if the initialambiguity is removed by creating a clause boundary for an embedded clause, SRCs become
easier to process compared to ORCs prior to the relativizer in Mandarin. However, such clear
and concrete evidence for an experience-based account has yet to be observed in Korean orother prenominal languages.

Integration-Based Models
For filler-gap dependencies (Chomsky 1965, 1981; Clifton and Frazier 1989; Fodor 1989;
Hawkins 1999), the head noun is required to be integrated with the gap to assume its
grammatical role within the RC; however, the mechanism for integration is not yet fully
understood, and there are several competing models within the literature (c.f., Gibson 2000;
Lewis and Vasishth 2005; O’Grady 1997). A basic principle for integration is that as the distance increases between the filler and the gap, integration becomes more difficult. Distance,
however, has been defined differently by different researchers. Specifically, distance has been
defined as: (1) linear-distance (Gibson 1998, 2000) based on the number of intervening syntactic dependencies on a linear plane, (2) temporal distance (Lewis and Vasishth 2005) basedon the amount of time between the filler and gap, and (3) structural-phrase distance (O’Grady
1997) based on the number of intervening structural-phrase nodes in syntactic structure. Fora language such as Korean, linear- and temporal-distance both would predict that integration
for ORCs should be easier than SRC integration. This is because there are less discourse
referents between the filler and gap. Meanwhile, the structural-phrase definition of distancepredicts that ORCs should be more difficult than SRCs, as there are more intervening structural phrases between the gap and the object head than between the gap and the subject head.
See Fig. 1 for an illustration of this.

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SRC: gapi senator-acc attack-adn reporteri -nom…

ORC: senator-nom gap i attack-adn reporteri-nom…

IP

CP
Opi

NP

VP

reporter i-nom

Jinju-acc saw

C'
IP

NP
NP

CP
Opi

NP
attacksenator-acc

senator-nom

NP

VP

reporter i-nom

Jinju-acc saw

C'IP-adnominal
VP

subject gapiIP-adnominal
VP

NP

attackobject gapi

Fig. 1 Basic syntactic structure for Korean relative clauses. The circles represent the syntactic phrases intervening between the filler and gap for each RC. The black arrows represent the general linear/temporal distance
between the filler and gap for each RC

Previous Findings in Korean
While Kwon and colleagues have effectively shown that ORCs are more difficult to process
than SRCs in Korean, a general issue with these studies is that there are far too many accounts
for this difficulty. In Kwon et al. (2010), experience, integration, similarity-based interference (Gordon et al. 2001) and successive NP marking (Lee et al. 2007; Nakayama et al.
2005) were all shown to contribute to ORC difficulty in eye-tracking studies. In temporarily
ambiguous structures, Kwon et al. (2010) claimed that this processing difficulty starts with
the introduction of the head noun. These findings, combined with Kwon et al. (2006) andKwon et al. (2013), which both revealed no reliable observation of ORC difficulty prior tothe head noun, would suggest that ORC difficulty in Korean begins at the head noun. As
such, Kwon and colleagues claim that the locus of disambiguation for Korean RCs is thehead noun. However, the following paragraphs describe how this point is debatable, giventhat adnominal markers likely correspond with an RC interpretation. This is supported bycorpora findings and experience-based models, both of which explain the ORC difficultyfound at the adnominal marker and how difficulty at the head noun most likely represent
effects of integration as defined by a structural-phrase metric.
As mentioned previously, the adnominal marker in Korean at the very least allows theparser to eliminate an incorrect matrix clause interpretation for the RC structure. Kwon andcolleagues hold the belief that the parser will wait until reading the head noun to construct a
new interpretation for the RC, as the adnominal marker does not guarantee a RC reading. Thisis because other embedded clauses can also be marked with the same adnominal marker, andthe surface structure of these clauses can appear nearly identical to an RC’s until the adnominal
marker. For instance, a fact-clause (see Kwon 2008, pp. 17–18) would appear identical to an
RC except that instead of a subject or object gap, there would be a null pronominal in theunderlying structure. The two clauses would differentiate at the head noun which would either
be a RC noun (e.g., gijaneun ‘reporter’) or a de facto expression (e.g., sasil ‘fact’). Kwon
(2008) reported that the average frequency of RC headed clauses (12,154 per million) is higher

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831

than fact-clauses (10,732 per million) within the Sejong corpus (see Kang and Kim 2004).
A log-likelihood test revealed this difference to be significant (χ 2 (1) = 88.41, p < .001).
Despite the two clause types being indistinguishable in ambiguous contexts at the embedded
verb (e.g., attack-ADN), under the experience-based framework and the assumption thatparsing is incremental and predictive (Kamide 2008; Kamide et al. 2003; Kamide and Mitchell1999) the parser would have a greater expectation of encountering the comparatively more
frequent RC structure, compared to the less frequent fact-clause. This expectation would beeither met or refuted when the parser encounters the head noun (Hale 2001, 2006; Levy
2008). Nevertheless, RCs would still be more difficult to parse at the head noun, compared
to a fact-clause. This is because RCs would have to undergo the integration of the filler andgap, whereas the fact-clause would not.
According to experience-based models of processing, if the parser is interpreting eachclause as an RC at the embedded RC verb, then the ORC condition will begin to experiencegreater processing difficulty since it is the less frequent structure compared to SRCs. In
fact, Kwon et al. (2010) was able to show marginal processing difficulty at the RC verb using
temporarily ambiguous contexts and a significant difference with unambiguous RCs, both via
regressive go-past measures (regression-path duration). Kwon et al. characterize this go-pastmeasure as a later stage of processing and believe that it represents general comprehensiondifficulty. Accordingly, they did not attribute the difficulty found at the RC verb during gopast exclusively to experience-based resources. However, go-past has the potential of being
interpreted as an early stage effect (c.f., Clifton et al. 2007) and it has been shown to be avaluable measure within other RC studies (Gordon et al. 2006; Staub 2010; Traxler et al.
2002). Considering that the head noun is not yet integrated into the sentence when the RCverb and the adnominal marker are read, there is nothing that could occupy the RC gap until
the head noun is encountered. As such, the increased distance of filler-gap dependencies
seems to be poorly suited to describe ORC difficulty at the RC verb before the reading of
the head noun within ambiguous contexts. Accordingly, we interpret their results at the RCverb in both ambiguous and unambiguous contexts to be representative of experience-based
effects which first appear due to the adnominal marker allowing for the disambiguation ofclause type.
While we hold the view that the adnominal marker would serve as a clause type disambiguation point and therefore would incur a surprisal cost for ORCs during disambiguation(Hale 2001; Levy 2008), we also maintain that ORC difficulty at the head noun is better
explained by structural-phrase integration. Specifically since RC clause type would likely beestablished at the adnominal marker, the head noun should not be a locus of high surprisal
for either RC type.
In summary, we assert that the processing of Korean RCs within a temporarily ambiguous
context should be reinvestigated to validate an experience-based resource account of ORC
processing difficulty prior to the reading of the head noun.

Current Study
The present study will further investigate Korean RCs using eye-tracking. The main focus of
this study is to confirm that the processing difficulty for temporarily ambiguous Korean ORCs
begins at the embedded RC verb, as predicted by experience-based accounts of processing.
A lesser aim of this study is to replicate the previous findings of Kwon and colleagues: we
expect to find ORC difficulty at the head noun as predicted by the structural-phrase integration metric. In other words, we aim to show that both experience-based models and thestructural-phrase integration model are accurate for Korean RC processing, and also that

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these effects appear at different loci. Accordingly, we presented participants with Koreansentences containing either an initially ambiguous SRC or ORC and used eye-tracking tomonitor reading. Unlike previous studies, we included a sentential-decision task about theoverall plausibility of the target sentence (i.e., whether the sentence can be acceptable/saidin the language without resorting to paranormal interpretations). We chose this approachover the typical post-sentence comprehension probe because there has been some indication that comprehension probes may be more task-demanding than is required to parse andcomprehend the sentence (Caplan et al. 2008).

Experiment: Sentential Judgment Task Using Eye-Tracking
The aim of the current study was to investigate whether Korean ORCs are more difficult
to process at the embedded RC verb than SRCs before the head noun is read. If this isso, this study can be understood as an indication of support for experience-based models
of processing. A sentential judgment task and eye-tracking methods were used to capture
eye-movements and reading times to reveal which RC type was more difficult to process.

Methods
Participants
Thirty-two native speakers of Korean were recruited from Nagoya University in Japan. Due
to calibration errors, one participant was removed from the study (N = 31). All participants
were either undergraduate or graduate students at the time of the study. Participants gave
informed consent and received monetary compensation.

Materials and Apparatus
Thirty-two experimental items containing RCs were created for this study. All RCs modified
the matrix subject of the sentence. Items were counterbalanced to ensure that a participant
would only view either the SRC or ORC variant for a given target. A SRC and its ORC
counterpart only differed in the case marking suffix at the end of the RC noun (SRC is
N-ACC & ORC is N-NOM). The head noun was always marked with nominative case.
All experimental items were designed to have a relatively simple structure. The RC only
contained the RC noun and verb, and the matrix clause consisted of the head noun, an adverb
and an intransitive verb. In Kwon et al.’s (2010) items, there was an additional argument
in both the RC and matrix clause. We used a simpler structure than their previous experiments because we wished to eliminate any processing difficulty related to parsing additional
arguments.
All nouns were proper first names (e.g., Jinju and Minji). See below for an example of an
item used in the study. The example below transliterates the target sentence into the Roman
alphabet. However, Korean speaking participants were shown sentences written in Hangul.
Since the secondary task was a sentential-correctness decision and all experimental items
were semantically correct (e.g., plausible) utterances in Korean, 32 additional RC items (SRC
= 16) were created that contained a semantically incorrect (implausible) verb at either the
RC verb or matrix verb.

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833

RC NounRC Verb

Head NounAdverbMatrix Verb

[jinju-lul/ka

seoldeugha-n]minji-kagyeolgugnawassda

eventuallycame.out

Jinju-ACC/NOM persuaded-ADN Minji-NOM‘Minji who persuaded Jinju (Jinju persuaded) eventually left.’

Stimulus sentences were displayed horizontally on the centre left of a 17-inch Mitsubishi
LCD monitor at a distance of 70 cm from the head and chin rest mount. All characters weredisplayed in Korean (Gulim 25pt; visual angle of 2.05◦ ). Eye movements were recorded using
an EyeLink 1000 Core System (desktop EyeLink 1000 SR Research Ltd., Ontario, Canada).
The resolution of the eye-tracker was 0.01◦ RMS, and the sampling rate was 1000 Hz (i.e.,measured every 1 ms). Only right eye-fixation data was collected. An attached gamepad wasused for button-response events.

Procedure
Participants were instructed to read Korean sentences displayed one at a time on a computer
monitor, and told that they would be asked to judge whether the sentence was semanticallycorrect (that is, able to be said or make sense in a real world setting without resorting toa paranormal interpretation) by pressing either the “True” or “False” marked buttons on
the gamepad. They were asked to read and judge the sentence as quickly and accurately
as possible while still maintaining accuracy and were given a maximum of eight seconds
to complete each item in the task. Eight practice items were given prior to the experiment
proper to ensure that the participants understood the task.
Prior to each experimental session, the camera was calibrated for each participant. This
was accomplished by a 9-point calibration method and subsequent validation. Calibration
was periodically repeated throughout each experimental session after block sessions (blocksof eight items) or when a participant was unable to accurately fixate on the mask (within a
block session). Prior to each trial, a drift-correction fixation mask was presented at the centre
left of the screen, the point at which the sentence would begin. Once the participant accurately
fixated on the mask, the proctor would remove the mask and display the trial sentence. The
participants then read each sentence and made their judgment using the gamepad (withineight seconds). After the button response, the stimulus item was immediately removed andno feedback was given. Reading times were measured from the onset of the stimuli to thebutton press response.

Eye-Tracking Measures
Reading time measures for the various processing stages (i.e., early and late) were collected
for each word of the sentence. For eye-tracking measures, we follow Clifton et al.’s (2007)
descriptions of eye-tracking. The earliest processing stage reported is first-fixation duration
which refers to the first fixation made in an interest region consisting of only a singular
fixation point. Next is first-pass reading time (RT) which is composed of all fixations madewithin an interest region from when the region is first entered (from the left) until the region
is exited in either direction (left or right). This measure can be a collection of one or more
fixation points; thus, it is equal to or greater than first-fixation duration. A key regression
measure reported in this study is go-past RT, the total reading of an interest region (e.g., RC
Verb) before the region is exited to the right (e.g., Head Noun) for the first time. This also
includes any regressive readings out of the region to the left (e.g., RC Noun) before going

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right. Therefore, go-past RTs are greater than or equal to first-pass RTs. The late processing
measure reported in this study is re-reading time, the sum of all fixations after first-pass RT
for an interest region (total time in the region minus first-pass RT). Additionally, regression–out (i.e., first-pass regression-out) proportion is reported where applicable. The total reading
time of the sentence and accuracy ratings are also reported.

Results
Prior to the analyses, five trials were removed due to participants failing to make a judgment
within the eight second trial period. For the remaining trials, all fixations below 80 ms
were merged into a neighbouring fixation within a one-character distance (72 fixations).
This was then followed by the removal of all remaining fixations under 80 ms and also
fixations that exceeded 1000 ms resulting in the removal of 824 fixation points (7.17% of all
fixations).
The collected reading times and binomial data (i.e., accuracy and regression-out) wereanalysed using linear mixed effect modelling (Baayen et al. 2008) and the lme4 package(Bates et al. 2014) within R (R Core Team 2014). For every analysis, the fixed effect was
RC type (ORC = −.5 & SRC = +.5) and the random effects were subjects and items(random intercept and slopes). Besides accuracy, all other analyses were done only on trials
with correct judgments. Reading times were transformed using their natural logarithm andanalysed with the lmer function with maximum likelihoods. Satterthwaite’s approximations
were used via thelmerTest package to generate p values for each model (Kuznetsova et al.
2014). For binomial data, the glmer function (binomial link function) was used to calculate
the z distribution using maximum likelihoods and Laplace approximations (Harding andHausman 2007; Jaeger 2008). Data outliers (RT data only) were trimmed based upon ±2.5
standard deviations of the predicted model which resulted in the elimination of 1.58% of thedata. In the sections below, the results of each region of the sentence is reported separately.
Refer to Table 1 for means and standard errors (natural log transformation for RTs) and Table
2 for the detailed results of the linear mixed effect modelling.

Sentence
The overall processing of sentences did not differ between conditions. While the total reading
time of all sentences revealed that the ORC condition was read more slowly than the SRC
condition, this effect was only marginal ( p = .077). In addition, the difference in judgment
accuracy between ORC (83%) and SRC (87%) types was not significant ( p = .281). Consequently, the overall processing data of the sentences alone could not reveal which condition
was more difficult to parse.

RC Noun (Jinju-ACC/NOM)
At the reading of the first region of the sentence, there were no significant differences between
conditions during first-fixation duration ( p = .247) or first-pass RT ( p = .388). As such,no difficulty was found for either condition during early measures of processing at the RC
noun. Re-reading time, however, revealed a marginal difference ( p = .082) between conditions, indicating that ORCs were read more slowly than SRCs during this later processing
stage.

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Table 1 Means for reading
times, accuracies, and regression
proportions

835
ORC
Means

SE

SRC
Means

SE

p value

Total time

7.71

0.02

7.66

0.02

p = .077

Accuracy

0.83

0.02

0.87

0.02

p = .281

Sentence

RC nounFirst-fixation

5.28

0.01

5.31

0.01

p = .247

First-pass

5.74

0.02

5.77

0.02

p = .388

Re-reading

5.88

0.04

5.77

0.04

p = .082

RC verb
First-fixation

5.38

0.02

5.35

0.02

p = .152

First-pass

5.56

0.02

5.51

0.02

p = .070

Re-reading

5.97

0.04

5.91

0.04

p = .226

Go-pass

5.76

0.03

5.66

0.03

p < .01

Regression-out

0.18

0.02

0.13

0.02

p = .378

Head nounFirst-fixation

5.40

0.02

5.36

0.02

p = .153

First-pass

5.59

0.02

5.59

0.02

p = .387

Re-reading

5.90

0.04

5.90

0.04

p = .846

Go-pass

5.78

0.03

5.68

0.03

p < .05

Regression-out

0.18

0.02

0.12

0.02

p = .169

AdverbFirst-fixation

5.43

0.02

5.44

0.02

p = .492

First-pass

5.54

0.02

5.52

0.02

p = .658

Re-reading

5.63

0.04

0.54

0.04

p = .797

Go-pass

6.23

0.04

6.08

0.04

p < .05

Regression-out

0.47

0.03

0.40

0.02

p < .05

Matrix verb
Reading times in logtransformations, accuracy andregression in frequency
proportion

First-fixation

5.29

0.03

5.32

0.03

p = .782

First-pass

5.42

0.04

5.45

0.03

p = .849

Re-reading

5.70

0.08

5.78

0.07

p = .265

Regression-out

0.75

0.03

0.77

0.03

p = .901

Embedded RC Verb (Persuaded-ADN)
For the RC verb, while first-past RT only displayed a marginal increase in RTs for the ORC
condition ( p = .077), go-past RT did reveal a significant difference between conditions( p < .01), demonstrating that participants spend more time reading ORCs before moving
onto the head noun. However, despite the significant difference in go-past RT, the regressionout proportion was not significantly different between conditions ( p = .378). Additionally,neither first-fixation duration ( p = .152) nor re-reading time ( p = .266) revealed any
significant differences in RTs between conditions. This suggests that ORC difficulty begins
during the early stages of processing, but that this difficulty does not persist on to later stages.
This difficulty likely subsides after the adnominal marker (e.g., attack-ADN) was read, since
first-fixation was not significant.

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Table 2 Linear mixed effectmodelling estimates and t/z
valuesJ Psycholinguist Res (2017) 46:827–845
EstimateSEDF

t/z value

Sentence
Total time−.04708.02526

20.58−1.86†

Accuracy

.6559

.6084

979.001.08

RC nounFirst-fixation.02548

.02

53.25

1.17

First-pass.02308

.03

28.26

0.88

Re-reading−.10003

.06

29.78

−1.803†First-fixation−.03513

.02

30.32

−1.47

First-pass−.05225.03

160.34−1.822†

RC verb

Re-reading−.07711

.06

29.92

−1.24

Go-pass−.09438.04

193.51−2.696**Regression-out−.2064.23

823.00−0.88

Head nounFirst-fixation−.03352

.02

20.46

−1.48

First-pass−.02489

.03

29.61

−0.88

Re-reading.01188

.06

32.01

0.20

Go-pass−.10758

.04

45.47

−2.475*Regression-out−.4583.33

820.00−1.38

AdverbFor reading time measures, anegative estimate indicates anincrease in reading time in logtransformed milliseconds for the
ORC condition. For accuracy andregression measures, a positive
estimate indicates an increase of
accuracy or probability ofregression. † < .1 * p < .05;** p < .01; *** p < .001

First-fixation.02048

.03

31.15

0.70

First-pass−.01521

.03

28.01

−0.45

Re-reading−.0157

.06

36.71

−0.26

Go-pass−.15575

.06

66.00

−2.532*

Regression-out−.4716.20768.00−2.393*Matrix verb
First-fixation

.01

.05

22.12

0.28

First-pass

.01

.0

26.41

0.19

Re-reading

.12

.10

17.05

1.15

Regression-out

.04

.33

534.000.12

Head Noun (Minji-NOM)
At the head noun, only go-past RT revealed a significant difference between conditions ( p <.05). It was found that ORCs required more regressive readings back into the RC structure
before moving into the adverb, compared with SRCs. First-fixation duration ( p = .153), firstpass RT ( p = .387), re-reading RT ( p = .846) and regression-out proportion ( p = .169)
were not found to be significantly different between conditions.

Adverb (Eventually)At the adverb, ORCs were read significantly more slowly than SRCs during go-past RT( p < .05) and were significantly more likely to regress-out back to a prior region ( p < .05).

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837

First-fixation duration ( p = .492), first-pass reading ( p = .658) and re-reading ( p = .797),
however, did not reveal any differences between conditions.

Matrix Verb (Came.out)
There were no significant differences between conditions during any reading time measure
at the matrix verb (first-fixation duration ( p = .782), first-pass reading ( p = .849) andre-reading ( p = .265) and regression-out proportion ( p = .901).

General Discussion
The purpose of this study was to replicate the previous findings which showed that Korean
ORCs are more difficult to process, compared to SRCs, and to provide a more detailed accountof how and why this processing difficulty occurs. More specifically, the chief aim of this study
was to demonstrate that ORC processing difficulty first arises after the disambiguation of thetemporarily ambiguous RC, as explained by experience-based models.
The overall results of this study clearly demonstrated that the ORC condition was moredifficult to process (i.e., required longer reading times) compared to its SRC counterpart.
This was clear at multiple positions, including the RC noun, embedded RC verb, the headnoun and the adverb region. This data strongly supports the general aim of the study. Similar
to Kwon et al. (2010), there are several explanations for the higher processing cost of ORCs:
experience-based effects (Hale 2001, 2006; Levy 2008; MacDonald and Christiansen 2002;
Mitchell et al. 1995), memory-based effects of structural-phrase integration (O’Grady 1997)and similarity-based interference (Gordon et al. 2001). However, unlike Kwon et al. (2010),
we are able to attribute these processing effects to different regions within the sentence.

Structural-Phrase Integration
At the parsing of the head noun, integration of the co-indexed filler and gap dependencies
occurs. However, as mentioned before, if this backwards anaphoric search for the gap utilizes alinear-based (Gibson 1998, 2000) or a temporal-based (Lewis and Vasishth 2005) mechanism,
then ORCs should actually be easier to process at the head noun since there is less intervening
discourse separating the filler and gap at the surface structure. However, according to thestructural-phrase integration model (O’Grady 1997), ORCs are more difficult to processsince there are more syntactic-phrases intervening between the filler and gap in ORCs thanin SRCs (refer to Fig. 1). Nearly identical to Kwon et al. (2010), go-past RTs in the current
study provide evidence for a structural-phrase integration model and cannot currently support
either the linear- or temporal-based models. Considering that Kwon et al. (2013) revealed thatthe difficulty at the head noun is similar to integration effects in English (Gouvea et al. 2010)
and Japanese (Ueno and Garnsey 2008), it is likely that integration-based effects are at least
partially inducing longer reading times for ORCs at the head noun. However, integrationeffects cannot account for the processing difficulty during go-past RT at the RC verb since it
is not the locus of integration in Korean RCs.
In the discussion below, we will eventually argue for an experience-based account at theembedded RC verb. However, it is not likely that experience-based effects are driving thedifficulty at the head. For instance, as revealed by Kwon (2008), RCs as a whole are moredifficult to process at the head than fact-clauses due to integration, despite the fact that RCs are

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a more frequent structure than fact-clauses. In the current study, if experience-based effects
were originating from the RC verb, we would expect these effects at the head noun to be seen
immediately. However, difficulty at the head noun did not begin until go-past reading. While
we argue that go-past should be considered an early measure of processing, go-past at thehead noun should be viewed differently than the significant difference during go-past at the
RC verb. This is because first-fixation and first-pass reading at the head noun failed to show
longer reading times for the ORC condition. Consequently, experience-based effects andintegration-based effects appear to be disassociated from each other at different loci within
the sentence. Because of this, we believe that both models are valid for Korean RC processing.
While the locus of integration appears at the head noun, the locus of experience-based effects
in Korean is found at the embedded-RC verb prior to its head.

Similarity-Based Interference
Under the framework of similarity-based effects (Gordon et al. 2001, 2006; Lee et al. 2007),storing multiple nouns with similar features into working memory creates a difficulty during
the retrieval of a noun. Since the RC noun in this study shared many of the same features as thehead noun for ORCs (i.e., case-marking, animacy and proper name), under this theory, these
two nouns compete with each other in working memory. This competition could increase theprocessing cost. This can be supported by the increased go-past RTs at the head noun andadverb. As Kwon et al. (2010) notes, having two successive nouns marked with nominative
case could also have increased RTs for ORCs at the head noun and prior regions during laterstages of processing. This would partially explain the longer re-reading RTs at the RC noun.
However, similar to integration-resources, similarity-based interference cannot explain the
difficulty for ORCs before the head noun was parsed (i.e., the go-past RT at the embedded
RC verb).

Experience-Based Effects
According to experience-based models of processing, less frequently occurring structures ina language will be more difficult to process than more frequently occurring structures (Hale2001, 2006; Levy 2008; MacDonald and Christiansen 2002; Mitchell et al. 1995). However,as mentioned before, in temporarily ambiguous structures, RC frequency effects will not
be observable until the structure is disambiguated. Accordingly, a lack of significant effects
during the early stages of processing at the RC noun and during first-fixation duration at
the RC verb (since multiple fixations are likely needed to read the verb and its morphology)
are not in conflict with experience-based models. This is because, at these early stages ofprocessing, the structure would likely still be ambiguous. All the effects found in this study
are potentially compatible with frequency-based effects. However, as previously mentioned,
the effects at the head noun and adverb regions are better explained by structural-phrase
integration-effects and similarity-based interference effects.
In order to observe experience-based effects of processing alone (i.e., without other contributing factors such as integration or similarity-based interference), it is necessary forreading times in the ORC condition to be longer, prior to the reading of the head noun. Since
this study used temporarily ambiguous RC structures, processing difficulty due to experiencebased effects of RC structure type should not occur until the parser has disambiguated the123

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839(correct) RC structure from a (more frequently seen, but incorrect) matrix clause interpretation. While there may be different loci of disambiguation for each clause type, it was likelythat readers could correctly predict the RC structure at the full reading of the embedded RC
verb (i.e., verb-adnominal) for both the RC types. Thus, because ORCs are less frequent in
Korean, they were more difficult to parse after disambiguation. This was indicated by thesignificant difference during go-past RT and the marginal difference in first-pass RT at the RC
verb. In addition, the difficulty found at the head noun, adverb and re-reading at the RC noun
indicate greater processing difficulty for the less frequent ORC structure. Accordingly, theseresults provide general support for experience-based models of processing. In the subsections
below, we discuss disambiguation and evidence for experience-based models.

The Locus of Disambiguation and Evidence for an Experience-Based AccountAs mentioned above, RCs in Korean have the potential to be initially ambiguous, meaningthat the parser would be unaware that the structure was a RC until a locus of disambiguation.
For ambiguous contexts, the first possible locus would be the adnominal marker suffixed tothe embedded verb (e.g., attack-ADN). While this locus would eliminate the matrix clauseinterpretation, the embedded clause would still be ambiguous, as there are other possible
embedded clauses in Korean, such as fact-clauses (e.g., subject-pro senator-ACC attackADN). As such, Kwon and colleagues claim that the parser needs to wait until the head noun,
allowing it to distinguish a fact-clause (e.g., sasil ‘fact’) from a RC (e.g., gijaneun ‘reporter’).
Admittedly, it is possible that since the two structures are too similar, the subject/object
asymmetry at the embedded verb can be explained by the general frequency of Korean
embedded clauses (which lack either an overt subject or object). This would, nevertheless,still support an experience-based account for the ORC difficulty at the embedded verb (e.g.,
attack-ADN). In other words, regardless of the initial interpretation made at the adnominal
marker, the processing difficulty for ORCs at this locus would still appear. However, we holdthe view that the structure would likely be interpreted as an RC. As previously mentioned,
Kwon had reported that the head of an embedded clause affixed with the adnominal marker
was more frequently an RC. Taking a more fine-grained approach, the parser would preferan RC interpretation here. Future studies focusing on the differences in processing between
fact-clauses and RCs prior to the head in Korean may be needed to clarify this.
Taking a look at because-clause structures in Korean (which are marked with—se‘because’), at the reading of the because-marker (e.g., attack-because), there is no longer
an ambiguity of clause type at the marker. In fact, Kwon (2008) was able to show a significant difference between subject/object null pronominals. This can be attributed to theextreme rarity of Korean null objects. Accordingly, experience-based models (Hale 2001,
2006; Levy 2008) seem to be an accurate predictor of processing difficulty for embedded
clause structures at the locus of the embedded verb and suffixed marker in the Korean language. However, it stands to the question if there are any other possibilities that might explain
the difficulty for ORCs prior to the head noun.
At the first reading of the RC noun, both the accusative and nominative marker can elicit
difficulty for SRCs and ORCs respectively. As Kwon et al. (Kwon 2008; Kwon et al. 2010,2013, 2006) discuss, while a sentential initial, accusative-marked NP may be more difficult
to process (since it would indicate either scrambling or a null subject), a nominative-marked
NP could also be difficult, since there is less predictability for a transitive verb than an
accusative NP. For the ORC condition, there could be some difficulty at a transitive verb
(prior to the reading of the adnominal marker) since the parser would have to posit a null
object pronominal. In summary, early SRC difficulty would be seen at the RC noun, and

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ORC difficulty would be seen at either or both the RC noun and verb. However, Kwon etal. (Kwon 2008; Kwon et al. 2010, 2013, 2006) and the current study did not observe any
initial difficulty for accusative- or nominative- marked NPs in the embedded clause, either
by self-paced reading, eye-tracking or ERP methods. As such, verb transitivity and a single
nominative marked NP may not be that difficult for the parser to handle. Though this has
already been argued by Kwon et al. (2013, p. 29), more studies on either Korean or Mandarin
are likely needed to clarify the strength, reliability and time-course duration that the effectsof case marking would have during sentence processing.
The current study reports slightly, but still critically, different results from previous studies
on Korean RCs. Because of this the following section will explain possible sources for thesedifferences.

Comparison to Previous Studies
In Kwon et al. (2006) and Kwon et al. (2013), there was no processing difficulty associatedwith the embedded RC verb when using both SPR and ERP. Furthermore, Kwon et al. (2010)
only revealed marginal effects for temporarily ambiguous structures at this position using
eye-tracking. From these results, Kwon and colleagues claim that disambiguation in Korean
does not occur until the head noun, a position where each study revealed significant findings.
There are four explanations as to why our findings may conflict with the previous studies:differences in (1) experimental technique, (2) task methodology, (3) materials and (4) the
analysis and interpretation of the results.
In the previous SPR and ERP studies, participants were only allowed to view a sentence
one word at a time. In other words, participants were incapable of re-reading previous regions.
For eye-tracking in general, go-past measurements have often been an important measure ofprocessing difficulty in RCs (Gordon et al. 2006; Kwon et al. 2010; Staub 2010; Traxler et al.
2002). Considering that Korean RCs are both prenominal and ambiguous, go-past may beconsidered as an early processing stage for Korean RCs. At the very least, go-past should beconsidered a highly indicative measure of RC processing difficulty, as both the current study
and Kwon et al. (2010) largely reveal ORC difficulty via go-past measures. Since SPR and
ERP techniques lack such a measure, it could be that it is more difficult to view a processing
cost at the RC verb within a moving-window paradigm.
Another difference between experiments was the secondary task method. The current
study admittedly used a method not frequently used in eye-tracking studies. However, we donot believe the use of a sentential judgment task has skewed our results in a way that would
make them misrepresentative. This is because the current study replicated the general findingsof Kwon and colleagues. As previously mentioned, the motivation for using this task in placeof comprehension probes was that comprehension probes may be a more demanding task,
as they require participants to store target items in memory for the purpose of answering
a question (Caplan et al. 2008); however, more studies are needed to show the detailed
relationship between task methodology and sentence processing.
Additionally, the current study used materials of a simpler structure than Kwon et al.
(2010). The motivation for using simpler structures was that Kwon et al.’s items may havebeen unnecessarily difficult for participants to process, given that they contained more information than was required to show the differences between RC types. Thus, we decided toremove extra arguments in both the RC and matrix clause. Since a simpler structure may beeasier to process than a more complex structure, simpler items may account for some of thedifferences between studies.

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Lastly, the current study and Kwon et al. (2010) may not differ entirely. In Kwon et al.
(2010), difficulty for ORCs was seen at the RC verb for ambiguous contexts, albeit marginally,
during go-past measures. Considering that Kwon et al. (2010) used classical ANOVA measures, it remains unseen whether or not their results would have reached significance if they
had adopted to use LME. Consequently, a main difference between the current study and theirresults could simply boil down to the statistical methods used. While Kwon et al. (2010) do
not fully commit to an experience-based account at the RC verb, we assert that this accountbest explains the ORC difficulty encountered during both studies. Also, it is possible that
our results are also compatible with Kwon et al.’s second experiment, which also featured
unambiguous RCs. A discussion on this will be given in the subsequent section.

The Issue with Ambiguity and Discourse Priming
While the current study only investigated RCs with a temporarily ambiguous structure, Kwon
et al. (2010) conducted a second eye-tracking experiment using facilitating contexts (i.e.,
discourse priming) that would disambiguate the RC. However, no processing difficulty basedon RC type was observed before the embedded RC verb in their study. This is peculiar, as
ORCs should be initially more difficult to process at the RC noun if the parser correctly
took an initial RC interpretation. Here, the case marker would disambiguate for RC type.
This means that ORCs should have a higher processing cost due to greater surprisal for the
structure (Hale 2001; Levy 2008). While it was shown that including a facilitating context
did indeed speed up the reading of the clause, no difference between RC types was shownprior to the RC Verb. Considering that the results of the current study and both of Kwon
et al.’s (2010) experiments are similar (i.e., marginally or significantly longer go-past times
for ORCs at the RC verb), it is not clear whether participants took an initial RC interpretationin Kwon’s study. In other words, the question remains whether discourse priming attenuatedthe expected difficulty for ORCs at the RC noun or whether the discourse did not prime
for an RC interpretation. If the latter is accurate, then the results of the current study and
Kwon et al. (2010) both can support the same claim that experienced-based effects are firstpredicted at the embedded RC verb for ORCs prior to the reading of the head noun underambiguous contexts. The current study cannot support either possibility, but evidence fromanother prenominal RC language may shed light on this issue.
Recently, there has been some criticism against discourse priming methods for prenominal
RCs. Gibson and Wu (2013), using this technique, found an ORC advantage for Mandarin Chinese RCs, which they claimed supported a linear-based integration mechanism and conflictedwith experience-based models (i.e., SRC advantage). However, Lin (2014) and Vasishth et al.
(2013) both provide evidence that Gibson and Wu’s (2013) observation is better explainedby thematic priming from the preceding discourse. As mentioned in the introduction, Jäger
et al. (2015), using the target sentences from Gibson and Wu (2013), revealed that if theinitial ambiguity is removed by creating a clause boundary for an embedded clause rather
than using the priming technique, SRCs would initially become easier to process in Mandarin
as explained by experience-based models. For Mandarin Chinese at the very least, removing
the initial clause type ambiguity can influence whether experience-based models correctlypredicted the data or not.
Since methodology may be a confound, we believe that more studies are needed, using both
ambiguous and unambiguous structures, to reveal a better account of processing for Korean
RCs prior to the head. Additionally, we feel that other methods in conjunction with discourse
priming may be needed to attenuate the initial clause type ambiguity found in Korean RCs
as well as RCs in other prenominal RC languages (e.g., Japanese and Mandarin Chinese).

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Experience-Based Effects in Other Prenominal Languages
Overall, experience-based processing costs for a less frequent structure at the locus of disambiguation within a temporarily ambiguous RC structure are common for prenominal
languages. As previously mentioned, several studies on Mandarin Chinese (Jäger et al. 2015;
Lin and Bever 2006; Qiao et al. 2012) show ORC difficulty at the disambiguating relativizer
morpheme or prior if the initial clause type ambiguity is attenuated. Both these effects are
predicted by experience-based models. Therefore, the current results at the RC verb appear
to be consistent with prior experience-based processing effects found in Mandarin Chinese
while adding support to the account for Korean.
However, there is at least one prenominal language that shows an opposite trend.
Carreiras et al. (2010) report that in Basque (i.e., Euskara), ORCs are easier to process
at the disambiguation region for their items, which happened to be the ultimate or penultimate word in the sentence, despite ORCs being less frequent. At first glance, this would
appear to be strong evidence against experience-based effects (Grodner and Gibson 2005;
Pickering et al. 2000). However, unlike Korean, Mandarin Chinese and Japanese, RC type
could not be distinguished easily in their study since a SRC or ORC interpretation was notpossible until the matrix verb. Carreiras et al. (2010, p. 83) themselves bring up that the SRC
difficulty may be likely due to a garden path effect for the SRC structure, which is causedby the ambiguity of the morphemes affixed to the RC noun, which assign number and indicate grammatical role. In other words, the morphemes on the RC noun for SRCs and ORCs
appeared identical (e.g., -ak ‘plural’ for SRCs and -a-k ‘singular+Subject’ for ORCs). Whatis more, this confound appears not to have been addressed in later experiments in their study.
Accordingly, it is difficult to understand their results as against experience-based models, atleast until future studies resolve this confound. It is our prediction that if this issue could
be resolved, then ORC difficulty would appear at the complementizer marker, which sits at
the right boundary of the RC. If this proves to be accurate, Basque would appear consistent
with Mandarin Chinese and Korean under the framework of experience-based models. For
ambiguous RCs in Japanese, however, there is not a way to view experience-based effects
prior to the head which is also the locus of integration. Consequently, it may be too difficult
to tease apart experience-based and integration-based resources at the head noun.
In summary, experience-based effects may be limited to or best seen at a locus of ambiguity
for RCs. However, they are nonetheless integral for the proper prediction of processing
difficulty within ambiguous and unambiguous RCs. Considering that there is also evidence
against frequency effects, we believe more studies are needed to investigate if there areunderlying factors which could explain whether or not experience based models are more
tightly connected to the processing of specific structure or contexts. Nevertheless, the current
study adds empirical evidence within a prenominal RC language to the growing body ofliterature supporting experience-based models for relative clause processing.

Conclusion
In this study, we sought out to support the claim that ORCs in Korean are more demanding
than SRCs with respect to processing. More specifically, we aimed to determine whether
experience-based accounts of processing can accurately predict greater difficulty for ORCs
before the reading of the head noun. Not only did the results support the main hypothesis,
we also replicated previous findings at the head noun, supporting the claim that integration

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in Korean likely uses a structural-phrase integration mechanism. In other words, the current
study adds to the previous literature by showing that the effects of integration and experienceare dissociated with each other and appear at separate loci within the sentence. Accordingly,
the current study adds support from the Korean language for an experience-based account at
the locus of disambiguation for RC processing similar to that of other prenominal languages
such as Mandarin Chinese. In conclusion, temporarily ambiguous ORCs first incur processing
difficulty at the locus of disambiguation as a result of being the less frequent structure prior
to the integration of the filler and gap dependencies.
Acknowledgements We would also like to thank the participants at the AMLaP 2015 ‘Architectures andMechanisms for Language Processing’ for their insightful comments. Additionally, we would like extend
our gratitude to our reviewer for their helpful comments on this paper. Lastly, we would like to express ourappreciation to Professor Sugiura of the Graduate School of International Development at Nagoya University
for allowing us to use his eyetracker. This study was funded in part by the Japan Society for the Promotion of
Science (JSPS) Grant Number 16K13242 (principal researcher: Katsuo Tamaoka), and the Grand-In-Aid for
JSPS doctoral course fellows granted to Michael P. Mansbridge (15J03336).
Compliance with Ethical Standards
Conflict of interest None.
Human and Animal Rights Statement All personal information collected from participants was stored ina secured location, and participants were given pseudonyms for data analysis purposes. Participants were
not subject to harm and could only experience mild discomfort from prolong seating or eye discomfort fromprolong reading.
Informed Consent In the current study, all participants gave informed consent and received monetary compensation.

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