Journal of Psycholinguistic Research, Vol. 34, No.3, May 2005 (© 2005)
DOI: 10.1007/s10936-005-3641-6

Priority Information Used for the Processing ofJapanese Sentences: Thematic Roles, Case Particles
or Grammatical Functions?
Katsuo Tamaoka,1,6 Hiromu Sakai,2 Jun-ichiro Kawahara,2
Yayoi Miyaoka,3 Hyunjung Lim,4 and Masatoshi Koizumi5
The present study investigated scrambling effects on the processing of Japanese sentences andpriority information used among thematic roles, case particles and grammatical functions. Reaction times for correct sentence decisions were signiﬁcantly prolonged for scrambled active sentences with transitive verbs in the ﬁrst experiment and with ditransitive verbs in the second
experiment. Errors were made with scrambled sentences more than canonical sentences in bothexperiments, which suggested that scrambling effects were apparent in active sentences. Passive
sentences in the third experiment indicated that canonical order deﬁned based on case particles,
not thematic roles, was more quickly and accurately identiﬁed than scrambled order. Potential
sentences in the fourth experiment and causative sentences in the ﬁfth experiment indicated thatthe processing of scrambled sentences based on grammatical functions, but not on case particles, required longer reaction times and resulted in higher error rates than canonical sentences.
Consequently, scrambling effects in the present study indicated that neither thematic roles norcase particles can provide fully-satisfactory information for canonical phrase order, and that
only grammatical functions offer satisfactory information in all types of sentences.
KEY WORDS: Japanese sentence processing; priority information; thematic roles; case particles;
grammatical functions.

1 International Student Center, Hiroshima University, Hiroshima, Japan.
2 Graduate School of Education, Hiroshima University, Hiroshima, Japan.
3 Hiroshima University of Economics, Hiroshima, Japan.
4 Graduate School for International Development and Cooperation, Hiroshima University,

Hiroshima, Japan.
5 Graduate School of Arts and Letters, Tohoku University, Sendai, Japan.
6 To

whom all correspondence should be addressed. International Student Center,
Hiroshima University, 1-1, 1-chome, Kagamiyama, Higashi-Hiroshima, 739-8524 Japan,
email: ktamaoka@hiroshima-u.ac.jp
2810090-6905/05/0500–0281/0 © 2005 Springer Science+Business Media, Inc.

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INTRODUCTION
Save for the rule that verbs must come at the end of sentences, word
order in Japanese sentences is ﬂexible. Studies in theoretical linguistics(e.g., Saito, 1985) present ample syntactic evidence for transformational
accounts of free word order in Japanese. According to these accounts,
canonical word order is reordered by a transformation called ‘scrambling’ (originally proposed by Ross, 1967; see general information aboutscrambling in Nakayama, 1999; Nemoto, 1999). Research in sentence processing, however, presents a conﬂicting picture on scrambling effects (seeMiyamoto, 2004 for overview). Chujo (1983) reported that reaction times
to make correct sentence decisions are lengthened by reordering phrases
by scrambling. Likewise, Mazuka et al. (2002) found scrambling effects
on Japanese sentence processing by way of an eye-movement experiment.
Conversely, Nakayama (1995) and Yamashita (1997) found no signiﬁcantscrambling effects using self-paced reading methods. To clarify these conﬂicting ﬁndings, the present study examined the effects of scrambling on
the processing of Japanese sentences, using active sentences with transitive
verbs in the ﬁrst experiment and ditransitive verbs in the second experiment. Once the scrambling effects on active sentences could be established,passive sentences in the third experiment, potential sentences in the fourthexperiment, and causative sentences in the ﬁfth experiment were examined by comparing canonical and scrambled word orders with the aim of
revealing priority of information used by native Japanese speakers for theprocessing of Japanese sentences.
‘Gap-Filling Parsing’ Hypothesis for Explaining Scrambling Effects
A ‘gap-ﬁlling parsing’ hypothesis was ﬁrst proposed for English(Frazier & Clifton, 1989), Dutch (Frazier & Flores d’Arcais, 1989) andlater also by some studies of Japanese Wh-scrambling constructions(Aoshima et al., 2002; Sakamoto, 2002). For example, a scrambled word
order in an active sentence with a transitive verb (V) is created by rearranging a subject (S) and an object (O): ‘Tadao deceived Yukiko’ iswritten in a canonical SOV sentence such as Tadao-ga Yukiko-o damashita and a scrambled OSV sentence such as Yukiko-o Tadao-ga damasita.
Chujo (1983) asked native Japanese speakers to judge whether sentences
made sense semantically by pressing a ‘Yes’ or ‘No’ button. Chujo foundthat scrambled sentences took longer to produce a correctness decision
than canonical sentences, which he explained as follows. If the nominative noun phrase (NP-ga) Tadao-ga is placed in its canonical position before the accusative NP-o Yukiko-o, speakers can comprehend thePriority Information Used for the Processing of Japanese Sentences283

sentence without any extra effort. However, when the accusative NP-o isplaced in the frontal position and NP-ga follows it (i.e., scrambled order),speakers must know whether or not the frontal accusative NP-o is appropriate for the object which typically appears just before the verb damashita to construct a verb phrase (VP) Yukiko-o damashita. The reversed orderof NP-o and NP-ga initiates a search for ‘gap’ which is originally placed
just before the transitive verb in canonical order. Due to this ‘gap-ﬁllingparsing’, speakers need extra time to process scrambled sentences.
On the other hand, Nakayama (1995) and Yamashita (1997) conducted on-line sentence processing experiments using self-paced reading
methods, which did not ﬁnd differences in reading times between canonical and scrambled sentences. According to these ﬁndings, both the nominative NP-ga and the accusative NP-o are located parallel to one another
under the single ﬂat level (i.e., ﬂat structure). Since there is no speciﬁccanonical order in the ﬂat structure, any word order can be generated toconstruct a sentence. Sakamoto (2001) further elaborated on the resultsof Yamashita, noting that since case particles are attached to all nouns
in Japanese, clear identiﬁcations are given to functions of nouns. Consequently, scrambled word order does not require an extra cognitive load
for sentence parsing. Given this argument, the assumption of ﬂat structure
does not initiate the gap-ﬁlling parsing. Since scrambling effects showed
mixed results in previous studies, the present study ﬁrst examines scrambling effects using active sentences with transitive and ditransitive verbs.
Three Information Cues for Predicting Canonical Noun Phrase Order
There are three possible information cues for canonical noun phrase
order used by native Japanese speakers. First, canonical order is predictedby ‘thematic roles’ in such a way that an agent precedes a theme. For
example, an agent Hanako-ga precedes a theme Taro-o in active sentenceswith canonical order Hanako-ga Taro-o nagutta. Second, ‘case particles’ ina noun phrase provide relations between a predicate and noun phrases:
The particle –ga assigns a noun phrase nominative while –o assigns anaccusative. In this case, Hanako is marked as a nominative noun phrase
by –ga and Taro as an accusative noun phrase by –o. As a result, thesentence interprets that Hanako made an action of hitting Taro. Third,
canonical order is established by grammatical functions in such a waythat the subject precedes the object. For the purpose of this paper, we
assume that grammatical functions are not primitive notions, rather they
are deﬁned in terms of syntactic conﬁgurations (see Chomsky, 1981). Froma more abstract perspective, in the syntactic structure of a simplex clause
without involving any transformation such as scrambling, subject (S) is

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the argument in the syntactically highest position; direct object (DO) isthe argument in the lowest position; indirect object (IO) is the argumentin the position hierarchically between subject and object. When it is notnecessary to distinguish between direct and indirect objects, we refer tonon-subject arguments simply as objects. Since a verb (V) appears at theend of a sentence in Japanese (i.e., a head-ﬁnal language), the syntacticallycanonical order is as follows: [S [IO [DO V]]]. In the sentence Hanako-ga
Taro-o nagutta, the noun phrase Hanako-ga is the subject and Taro-o is theobject. Syntactically non-canonical orders (e.g., Taro-o Hanako-ga nagutta)
require gap-ﬁlling parsing, as mentioned above.
If results from the ﬁrst and second experiments demonstrate extra
cognitive loading for scrambled in comparison to canonical noun phrase
order in sentence processing (i.e., scrambling effects), all three information cues can be applied to predict the canonical noun phrase orderof active sentences. The third experiment used passive sentences such as
Taro-ga Hanako-ni nagurareta (‘Taro was hit by Hanako’). In this typeof sentence, scrambled order is created by swapping two noun phrases
as Hanako-ni Taro-ga nagurareta. The same meaning is kept in bothsentences. Interestingly, according to thematic roles, canonical order ispredicted as Hanako-ni Taro-ga nagurareta because an agent Hanako-ni
precedes a theme Taro-ga. In contrast, as a noun phrase with the nominative case particle –ga precedes a noun phrase with the accusative caseparticle –o, case particles provide the canonical noun phase order of thepassive sentence as Taro-ga Hanako-ni nagurareta. Grammatical functions
also provide information cues for canonical order in the same way ascase particles. Thus, canonical noun phrase order is different between thematic roles and case particles, and between thematic roles and grammatical
functions. Tentatively deﬁning the canonical noun phrase order as Taro-ga
Hanako-ni nagurareta, if the third experiment were to reveal scrambling
effects, thematic roles would be excluded while case particles and grammatical functions would remain as candidates of priority information in
determining canonical order.
The fourth experiment used potential sentences such as Taro-ni eigo-ga
hanaseru-daroo-ka? (‘Can Taro speak English?’). The canonical order insuch potential sentences is predicted by grammatical functions as Taro-ni
eigo-ga hanaseru-daroo-ka? because the subject Taro-ni precedes the object
eigo-ga. In contrast, prediction by case particles speciﬁes the canonicalorder as Eigo-ga Taro-ni hanaseru-daroo-ka? Unlike in active and passive
sentences, a noun with the dative case particle –ni is the subject in potential sentences (Harada, 1977; Shibatani, 1978; Ura, 1999). Thus, case particles provide information for canonical order other than grammatical roles
in potential sentences. Comparing the sentence processing of two different

Priority Information Used for the Processing of Japanese Sentences285

noun phrase orders, the fourth experiment excludes one of the possible
information cues. Since the fourth experiment compared the effects ofgrammatical function and linear ordering of the nominative and dative
case particles, the ﬁfth experiment investigated the effect of other two caseparticles of dative and accusative. The results of the ﬁfth experiment conﬁrm the conclusion from the previous experiments and generalize them toall types of case particles.
Outline of the Five Experiments
It was hypothesized that if scrambling effects were observed in theprocessing of the active sentences of the ﬁrst and second experiments, theresults would support all three information cues: thematic roles, case particles and grammatical functions. If the effects were observed in the passive
sentences of the third experiment, the ﬁrst information cue of thematicroles would be excluded. Finally, the fourth experiment with potential sentences and the ﬁfth experiment with causative sentences would determine
which type of information, case particles or grammatical functions, is theprimary factor affecting the speed and accuracy of processing sentenceswith different noun phrase orders.

EXPERIMENT 1: ACTIVE SENTENCES WITH TRANSITIVE
VERBS
The ﬁrst experiment tested whether native Japanese speakers takelonger to process active transitive sentences in scrambled noun phrase
order than those in canonical order. For example, an active sentence containing a transitive verb, such as Hanako-ga Taro-o nagutta (‘Hanako
hit Taro’) can be reordered by scrambling the subject and the object as
Taro-o Hanako-ga nagutta. Nevertheless, both the canonical and scrambled sentences have the same meaning. If scrambling effects are apparent,
these sentences must have a conﬁgurational structure as depicted in Fig. 1.
Figure 1(i) describes canonical order while Fig. 1(ii) scrambled order. The
transitive verb nagutta constructs a VP with the accusative noun phrase(NP-o) Taro-o. Once NP-o is placed in the initial position and the NP-ga
follows it, native Japanese speakers initiate a search for ‘gap’ which produces VP with the verb. This gap-ﬁlling parsing requires extra sentence
decision time. However, if no scrambling effects are found in sentence processing, such a structure may not exist and it would therefore be possiblethat noun phrases of NP-ga and NP-o are located parallel to one another.

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S

NP- gaVP

Hanako-ga
NP-oV

Taro-onagutta(i) Canonical Order
S

NP-o

S

Taro-oNP-ga

VP

Hanako-ga

A gap-filling parsing

NP-o

V

gap

nagutta(ii) Scrambled Order
Fig. 1. A gap-ﬁlling parsing in an active sentence with a transitive verb Hanako-ga Taro-onagutta (Hanako hit Taro).
Note: NP-ga refers to a nominative case-marked noun phrase. NP-o refers to an accusative
case-marked noun phrase.

MethodParticipants
Twenty-eight graduate and undergraduate students (22 females and6 males) at Hiroshima University in Japan, all native speakers of Japanese, participated in the ﬁrst experiment. Ages ranged from 21 years and
1 month to 29 years and 0 months, with the average age being 23 years and2 months on the day of testing.

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287

Materials
As listed in Appendix A, 52 correct, 32 incorrect and 20 control sentences (a total of 104 sentences) were prepared for the sentence correctness
decision task. Correct ‘Yes’ responses consisted of 52 active sentences withtransitive verbs. These 52 sentences were arranged in canonical order, andthe nominative case marked subject (NP-ga) and the accusative case marked
object (NP-o) were then swapped to create sentences of scrambled order. For
example, a sentence Tomoko-ga Taro-o hometa (‘Tomoko admired Taro’) wasaltered to Taro-o Tomoko-ga hometa. Since a pair of canonical and scrambled sentences was identical in terms of words used, a difference in syntactic
structure can be directly compared in reaction times and error rates.
It was expected that reading times would become shorter when participants saw sentences containing the same words. Thus, in order to prevent
this problem of repeatedly encountering the same words, a counterbalanced
design was used to assign participants to different words. Two lists of sentences were given to two groups of participants. Each list consisted of 52
sentences (26 canonical and 26 scrambled) for correct ‘Yes’ responses.
Thirty-two syntactically or semantically incorrect sentences were used
for correct ‘No’ responses to the task. As with sentences with correct‘Yes’ responses, scrambled sentences were created on the basis of canonical sentences. For example, the phrase order of a canonical sentence
Junko-ga Kenji-o nutta (‘Kenji stitched Junko’) was re-arranged to read
Kenji-o Junko-ga nutta. This counterbalanced design was also used for sentences with correct ‘No’ responses: Two lists of sentences were given to
two groups of participants. Each list consisted of a total of 32 sentences(16 canonical and 16 scrambled) for correct ‘Yes’ responses.
In addition, 20 control sentences were added to each of the two stimulus lists. The same control sentences were used for the two stimulus lists.
Consequently, a total of 104 sentences in each list consisted of 52 correct(26 canonical and 26 scrambled), 32 incorrect (16 canonical and 16 scrambled), and 20 control sentences.

Procedure
The presentation was controlled by a computer program Microsoft
Visual Basic 6.0 + Microsoft DirectX8. Stimuli with both ‘Yes’ and ‘No’correct responses were presented to participants in random order in thecenter of a computer screen 600 ms after the appearance of an asterisk ‘*’
indicating an eye ﬁxation point. Participants were instructed to respondas quickly and as accurately as possible in deciding whether or not thesentence made sense. Response was registered by pressing a ‘Yes’ or ‘No’

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288

button. Twenty practice trials were given to the participants prior to thecommencement of actual testing.
Analysis and Results
Extremes among sentence correctness decision times (less than 400 ms
and longer than 4000 ms) were recorded as missing values. The means ofcorrect ‘Yes’ and ‘No’ reaction times and error rates for sentence correctness decisions are presented in Table I. Before performing the analysis,reaction times outside of 2.5 standard deviations at both the high and low
ranges were replaced by boundaries indicated by 2.5 standard deviations
from the individual means of participants in each category. The statistical tests which follow analyze both subject (F 1) and item (F 2) variability.
Only stimulus items of correct responses were used in the analyses of reaction times.
A series of one-way analyses of variance (ANOVAs) with repeatedmeasures in canonical and scrambled noun phrase order were conducted
on reaction times (milliseconds) and error rates (percents), using subject(F1 ) and item (F2 ) variabilities. The ﬁrst experiment of active sentenceswith transitive verbs indicated that for correct ‘Yes’ responses, sentenceswith canonical order resulted in shorter reaction times [F1 (1, 27) = 58.90,
p < 0.001;F2 (1, 51) = 61.88, p < 0.001] and lower error rates [F1 (1, 27) =15.71, p < 0.001; F2 (1, 51) = 17.14, p < 0.001] than those with scrambled
order. The same ANOVAs were carried out for correct ‘No’ responses.
Sentences with canonical order processed shorter reaction times than thosewith scrambled order in subject analysis [F1 (1, 27) = 14.49, p < 0.001],
but not in item analysis [F2 (1, 31) = 0.02, n.s.]. Thus, some items muststrongly affect the results of reaction times for ‘No’ responses. On theother hand, error rates for correct ‘No’ responses indicated no signiﬁcantmain effect in subject and item analysis [F1 (1, 27) = 0.05, n.s.; F2 (1, 31) =1.56, n.s.].
Table I. Reaction Times and Error Rates for Active Sentences with Transitive Verbs
Reaction time (ms)Response type

Sentence type

Error rate (%)

M

SD

M

SD

‘Yes’
Responses

SOV
OSV

1209
1432

238
308

3.02
9.07

3.37
6.96

‘No’
Responses

OSV-SOVSOVOSVOSV-SOV

223
1297
1388
91

224
216

4.91
9.38

6.04
6.96
9.95
4.47

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289

Discussion
Experiment 1 revealed scrambling effects on the processing of active
sentences with transitive verbs for correct ‘Yes’ responses. This result supports that these sentences have a conﬁgurational syntactic structure forcanonical order as depicted in Fig. 1(i). For the processing of scrambled
sentences, the accusative NP-o, which is placed in the sentence-initial position, initiates search for ‘gap’ to complete the verb phrase constructedby NP-o (i.e., ‘gap’) and a transitive verb as shown in Fig. 1(ii). This
gap-ﬁlling parsing must lead to longer reaction times for scrambled sentences than canonical sentences. Some confusion involved in this parsing
process resulted in higher error rates for scrambled sentences than canonical ones, whereas this tendency was not observed in sentence correctness
decisions for correct ‘No’ responses. Since these sentences contained syntactic or semantic errors, the gap-ﬁlling parsing did not make a difference
between canonical and scrambled sentences.

EXPREIMENT 2: ACTIVE SENTENCES WITH DITRANSITIVEVERBSAs discussed in the introduction, there are conﬂicting results forscrambling effects on sentence processing. Although active sentences withtransitive verbs showed signiﬁcant scrambling effects in the ﬁrst experiment, an additional experiment was conducted to ascertain the effects
in different conditions. Therefore, the second experiment used active sentences containing ditransitive verbs such as Hanako-ga Taro-ni hon-okaeshita (‘Hanako returned a book to Taro’) as represented by the canonical sentence in Fig. 2(i). This type of sentence can exchange three nounphrases in any order, so that six different word orders can be produced
as one canonical and ﬁve scrambled sentences. These sentences still impart
the same meaning. In the present study, as depicted in Fig. 2(ii), an inanimate (i.e., the thirdly-positioned) NP-o noun phrase is placed in the sentence-initial position as in hon-o Hanako-ga Taro-ni kaeshita. If scrambling
effects are observed in the second experiment in addition to the ﬁrst, then,the gap-ﬁlling parsing must play a role in the processing of scrambled sentences with ditransitive verbs as well as those with transitive verbs.
MethodParticipantsSame as Experiment 1.

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S

NP-ga

VP

Hanako-ga
Animate NP-ni

V'

Taro-ni
Inanimate NP-o

V

hon-o

kaesita(i) Canonical OrderS

Inanimate NP-o

S

hon-o
NP-ga

VP

Hanako-ga
Animate NP-ni

V'

Taro-ni
Inanimate NP-oVgapkaesita

A gap-filling parsing(ii) Scrambled Order
Fig. 2. A gap-ﬁlling parsing in an active sentence with a ditransitive verb Hanako-ga Taro-ni
hon-o kaesita (Hanako returned a book to Taro).
Note: NP-ga refers to a nominative case-marked noun phrase. NP-o refers to an accusative
case-marked noun phrase. NP-ni refers to a dative case-marked noun phrase.

Materials
As listed in Appendix B, 20 correct, 20 incorrect and 20 control sentences (a total of 60 sentences) were prepared for the second experiment.

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291

Correct ‘Yes’ responses consisted of 20 active sentences with ditransitive verbs, which were arranged in canonical order. The nominative casemarked subject (NP-ga) and the inanimate accusative case marked object(NP-o) were then swapped to create sentences of scrambled order. For
example, a sentence Kenji-ga Junko-ni hana-o okutta (‘Kenji sent followers
to Junko’) was altered to hana-o Kenji-ga Junko-ni okutta. Since the canonical and scrambled sentences were identical in terms of words used, adifference in syntactic structure can be directly compared in reaction times
and error rates. Again, as in the ﬁrst experiment, a counterbalanced design
was used to assign participants to different sentences to avoid repeatedly
showing the same words. Two lists of sentences were given to two groupsof participants. Each list consisted of 20 sentences (10 canonical and 10
scrambled) for correct ‘Yes’ responses.
Twenty syntactically or semantically incorrect sentences were used forcorrect ‘No’ responses to the task. Scrambled sentences were created on
the basis of canonical sentences. For example, the phrase order of thecanonical sentence Kazuko-ga Kenji-ni senttaki-o odotta (‘Kazuko danced
a washing-machine to Kenji’) was re-arranged to senttaki-o Kazuko-ga
Kenji-ni odotta. The counter balanced design was also used for sentenceswith correct ‘No’ responses: Two lists of sentences were given to twogroups of participants. Each list consisted of a total of 20 sentences (10canonical and 10 scrambled) for correct ‘No’ responses.
In addition, the same 20 control sentences were added to each of thetwo lists. Consequently, a total of 60 sentences in each list consisted of 20
correct (10 canonical and 10 scrambled), 20 incorrect (10 canonical and 10
scrambled), and 20 control sentences.
ProcedureSame as Experiment 1.
Analysis and Results
Extremes among sentence correctness decision times (less than 400 ms
and longer than 5000 ms) were recorded as missing values. The means ofcorrect ‘Yes’ and ‘No’ reaction times and error rates for sentence correctness decisions are presented in Table II. Before performing the analysis,reaction times outside of 2.5 standard deviations in both the high and low
ranges were replaced by the boundaries indicated by 2.5 standard deviations from the individual means of participants in each category. Only
stimulus items of correct responses were used in the analyses of reaction
times.

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Table II. Reaction Times and Error Rates for Active Sentences with Ditransitive
Verbs
Reaction time (ms)Response type

Sentence type

M

SD

‘Yes’
Responses

SO1 O2 V
O2 SO1 V

1359
1963

320
643

O2 SO1 V-SO1 O2 V

604

‘No’
Responses

SO1 O2 V
O2 SO1 V

1436
1597

O2 SO1 V-SO1 O2 V

161

Error rate (%)
M

SD

1.79
11.79

3.90
17.44

10.00
265
398

1.79
4.29

4.76
10.34

2.50

As in the ﬁrst experiment, ANOVAs with repeated measures incanonical and scrambled sentences were conducted on reaction times anderror rates for correct ‘Yes’ responses. Again, the second experiment ofactive sentences with ditransitive verbs showed signiﬁcant main effects on
both reaction times (F1 (1, 27) = 56.36, p < 0.001; F2 (1, 19) = 70.25, p <0.001) and error rates (F1 (1, 27) = 10.80, p < 0.001; F2 (1, 19) =24.18, p < 0.001). The results revealed that the processing for scrambled sentences took longer reaction times and resulted in higher error rates
than canonical sentences. The same ANOVAs were carried out for correct ‘No’ responses. Canonical sentences were processed more quickly thanthose with scrambled order in subject (F1 (1, 27) = 16.07, p < 0.001) anditem (F2 (1, 19) = 8.58, p < 0.01) analysis. However, error rates for correct‘No’ responses indicated no signiﬁcant main effect (F1 (1, 27) = 3.10, n.s.;
F2 (1, 19) = 3.20, n.s.).
Discussion
The results of the second experiment for correct ‘Yes’ responses replicated those of the ﬁrst experiment. The processing of scrambled sentences was slower and yielded higher error rates when compared to thatof canonical sentences. Consequently, as shown in Fig. 2, active sentenceswith ditransitive verbs must form conﬁgurational structures as well as
those with transitive verbs. Again, the second experiment suggested gapﬁlling parsing performed for scrambled sentences as depicted in Fig. 2(ii).
Interestingly, there was a large difference in reaction times between canonical and scrambled sentences. The time for ones with ditransitive verbs
was 604 ms (see Table II), which was far longer than the 223 ms for ones
with transitive verbs (see Table I). This difference in the scrambling effecton the sentence processing between transitive and ditransitive verbs wasPriority Information Used for the Processing of Japanese Sentences293

produced by differences in the distance of the scrambling; a long distancescrambling was used for sentences with ditransitive verbs while a short distance scrambling for ones with transitive verbs.
As opposed to the ﬁndings of the ﬁrst experiment, the results forcorrect ‘No’ responses (i.e., incorrect sentences) in the second experiment revealed scrambling effects: scrambled sentences were processed more
slowly than canonical sentences. A difference in the distance probably created a longer parsing time for scrambled sentences with ditransitive verbs
for correct ‘No’ responses. Again, the difference in reaction times between
canonical and scrambled sentences was longer for ditransitive verbs thantransitive verbs: 91 ms (non-signiﬁcant) in the ﬁrst experiment, 161 ms(signiﬁcant) in the second experiment. Since neither experiment indicateddifferences in error rates, the longer distance in structure did not seem toinﬂuence the accuracy of processing for scrambled sentences for correct‘No’ responses of both transitive and ditransitive verbs.

EXPERIMENT 3: PASSIVE SENTENCES WITH TRANSITIVEVERBS
In the ﬁrst and second experiments, active sentences with transitiveand ditransitive verbs supported the existence of scrambling effects. Upon
proving these, the question arose as to what kind of information cues
native Japanese speakers use for identifying canonical noun phrase order.
There are three possibilities for active sentences: thematic roles, case particles and grammatical functions. Using the example in Fig. 2, thematicroles provide information that an agent Hanako returns to a goal Taro atheme hon (‘book’). Case particles provide information for canonical order
as a nominative noun phrase Hanako-ga, a dative noun phrase Taro-ni,
and an accusative noun phrase hon-o. Grammatical functions show nounphrases from the initial position in the conﬁgurational structure: a subject Hanako-ga, an indirect object Taro-ni, a direct object hon-o, and a
predicate kaeshita (‘returned’) at the end of the sentence. All three linguistic explanations provide appropriate information for canonical orderof active sentences. Table III summarizes predicted canonical noun phrase
orders, for the purpose of sentence processing, determined based on thethree information cues.
To determine priority information used for native Japanese speakers, the third experiment employed passive sentences with transitive verbs,
whereby thematic roles and case markers provided a conﬂicting picture.
Figure 3 gives an example of a passive sentence Taro-ga Hanako-ni
nagurareta (‘Taro was hit by Hanako’).

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Table III. Information Cases and Predicted Canonical Noun Phrase Orders
Information cases

Predicted canonical noun phrase orders

Thematic roles
Case particles
Grammatical functions

Agent > Goal > Theme
Nominative > Dative > Accusative
Subject > Indirect object > Direct object

S

NP-ga

VP

Taro-gaNP-ni

Vnagurareta

Hanako-ni(i) Canonical Order
S

NP-ni

S

Hanako-ni
NP-ga

VP

Taro-ga
NP-ni
A gap-filling parsinggap

Vnagurareta(ii) Scrambled Order

Fig. 3. A gap-ﬁlling parsing in a passive sentence with a transitive verb Taro-ga Hanako-ni
nagurareta (Taro was hit by Hanako).

Thematic roles provide information that the agent NP follows thetheme NP, so that an agent Taro-ni precedes a theme Hanako-ga, predicting the canonical order as Hanako-ni Taro-ga nagurareta. Assuming
the existence of scrambling effects on the processing of passive sentences,
if native Japanese speakers follow information guided by thematic roles,

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the canonical order of Hanako-ni Taro-ga nagurareta would be processedmore quickly and accurately than the scrambled order of Taro-ga Hanako-ni nagurareta. However, the canonical order is deﬁned by case particles as a noun with the nominative case particle –ga preceding a noun
with the dative case particle –ni. Thus, case particles deﬁne the canonical order as Taro-ga Hanako-ni nagurareta in Fig. 3(i) and the scrambled
order as Hanako-ni Taro-ga nagurareta in Fig. 3(ii). The prediction for sentence processing is then reversed in a way that the canonical order Taro-ga
Hanako-ni nagurareta should be processed more quickly and accurately
than Hanako-ni Taro-ga nagurareta. The third experiment offers an answer
as to which type of information, thematic roles or case particles, is actually used by native Japanese speakers.
MethodParticipants
Twenty-four graduate and undergraduate students (9 females and 15
males, none of whom participated in the ﬁrst and second experiments) at
Hiroshima University in Japan, all native speakers of Japanese, participated in the third experiment. Ages ranged from 21 years and 8 months to
31 years and 8 months, with the average age being 26 years and 5 months
on the day of testing.
Materials
As listed in Appendix C, 36 correct, 20 incorrect and 16 control sentences (a total of 72 sentences) were prepared for the third experiment.
Correct ‘Yes’ responses consisted of 36 passive sentences with transitive
verbs. These 36 sentences were arranged in canonical order based on caseparticles, the nominative case marked noun phrase (NP-ga) and the dative
case marked noun phrase (NP-ni) were then swapped to create scrambled sentences. For example, a sentence Junko-ga Kenji-ni osareta (‘Junko
was pushed by Kenji’) was altered to read Kenji-ni Junko-ga osareta. Yet,these two sentences carry the same meaning, so that a difference in syntactic structure can be directly compared in reaction times and error rates.
Again, as in the previous two experiments, to avoid repeatedly showing thesame words, a counterbalanced design was used to assign different sentences to participants. Two lists of sentences were given to two groupsof participants. Each list consisted of 36 sentences (18 canonical and 18
scrambled) for correct ‘Yes’ responses.
Twenty syntactically or semantically incorrect sentences were used forcorrect ‘No’ responses to the task. Scrambled sentences were created on

Tamaoka et al.

296

the basis of canonical sentences. For example, phrase order of canonicalsentence sora-ga Junko-ni sentakusareta (‘Sky was washed by Junko’) was
re-arranged to Junko-ni sora-ga sentakusareta. The counterbalanced design
was also used for sentences with correct ‘No’ responses: Two lists of sentences were given to two groups of participants. Each list consisted of a
total of 20 sentences (10 canonical and 10 scrambled) for correct ‘No’
responses.
In addition, 16 control sentences were added to each of the two lists.
Consequently, a total of 72 sentences in each list consisted of 36 correct(18 canonical and 18 scrambled), 20 incorrect (10 canonical and 10 scrambled), and 16 control sentences.
ProcedureSame as Experiments 1 and 2.
Analysis and Results
Extremes among sentence correctness decision times (less than 400 ms
and longer than 4000 ms) were recorded as missing values. The means ofcorrect ‘Yes’ and ‘No’ reaction times and error rates for sentence correctness decisions are presented in Table IV. Before performing the analysis,reaction times outside of 2.5 standard deviations at both high and low
ranges were replaced by boundaries indicated by 2.5 standard deviations
from the individual means of participants in each category. Only stimulus
items of correct responses were used in the analyses of reaction times.
As in the previous two experiments, ANOVAs with repeated measuresin canonical and scrambled sentences were conducted on reaction times
and error rates for correct ‘Yes’ responses. Passive sentences in the third
experiment indicated scrambling effects in both reaction times (F1 (1, 23) =Table IV. Reaction Times and Error Rates for Passive Sentences with Transitive
Verbs

Response type

Sentence type

Reaction time (ms)Error rate (%)

M

SD

M

SD

‘Yes’
Responses

SOV
OSV

1521
1722

359
497

1.85
6.25

3.54
8.08

‘No’
Responses

OSV-SOV
SOV
OSV

201
1484
1582

309
366

4.40
10.83
9.17

9.74
10.60

OSV-SOV

98−1.60Priority Information Used for the Processing of Japanese Sentences297

17.22, p < 0.001; F2 (1.35) = 16.23, p < 0.001) and error rates (F1 (1, 23) =10.18, p < 0.01; F2 (1.35) = 11.33, p < 0.01). The results suggested thatcanonical order deﬁned by case particles was processed faster and moreaccurately than scrambled order (see Fig. 3). The same ANOVAs were carried out for correct ‘No’ responses. Neither reaction times (F1 (1, 23) =2.67, n.s.; F2 (1, 19) = 2.06, n.s.) nor error rates (F1 (1, 23) = 0.19, n.s.;
F2 (1.19) = 0.61, n.s.) showed signiﬁcant main effects. Thus, no scrambling
effects were observed for correct ‘No’ responses.
Discussion
In passive sentences, the nominative case particle –ga comes before
the dative case particle –ni (i.e., case particles) while the agent comes
after the theme (i.e., thematic roles). The results of the third experiment indicated that canonical order deﬁned based on case particles wasmore quickly and accurately identiﬁed than scrambled order. As shownin Fig. 3(ii), the gap-ﬁlling parsing must take place under the conﬁgurational structure described by case particles. The sentence-initially positioned dative NP-ni Hanako-ni initiates a search for ‘gap’ to match theverb nagurareta (‘being hit’). Since grammatical functions also provide
the same information as case participles, the results of the third experiment excluded the possibility of thematic roles as priority information forcanonical order and supported the priority of case particles.
EXPERIMENT 4: POTENTIAL SENTENCES
The third experiment eliminated thematic roles as a candidate for priority information in sentence processing. Subsequently, the fourth experiment investigated which of the two remaining information cues, caseparticles or grammatical functions, is the primary factor. Potential sentences such as Hanako-ni eigo-ga hanaseru-darooka (‘Can Hanako speak
English?’) supply conﬂicting circumstances between case particles andgrammatical functions. In potential sentences, as the dative case particle –ni is assigned to syntactic subject properties, grammatical functions tell that a subject with -ni comes before an object with –ga in the
canonical order. On the other hand, case particles indicate noun phrase
order that a nominative case particle –ga should precede a dative particle–ni. Figure 4(i) describes the canonical order of potential sentences basedon grammatical functions. If the order of the phrase, Hanako-ni eigo-ga
hanaseru-darooka is processed faster and more accurately than eigo-ga Hanako-ni hanaseru-darooka (i.e., scrambling effects), grammatical functions
will be the last remaining source for canonical order. In this case, asTamaoka et al.

298

S

NP-ni

VP

Hanako-ni
NP-ga

Veigo-gahanaseru(+darooka)(i) Canonical Order
S

NP-ga

S

eigo-ga
NP-ni

VP

Hanako-ni
NP-ga
A gap-filling parsinggapV
hanaseru(+darooka)(ii) Scrambled Order
Fig. 4. A gap-ﬁlling parsing in a potential sentence Hanako-ni eigo-ga hanaserudarooka(Can Hanako speak English?).

depicted in Fig. 4(ii), native Japanese speakers will start searching for ‘gap’
soon after seeing the initially-positioned NP-ga eigo-ga (‘English’). However, if the results are reversed, case particles are the priority information
for canonical order provided to native Japanese speakers.
MethodParticipants
Twenty-four graduate and undergraduate students (15 females and 9
males, none of whom participated in the previous three experiments) at
Hiroshima University in Japan, all native speakers of Japanese, participated in the fourth experiment. Ages ranged from 19 years and 7 months

Priority Information Used for the Processing of Japanese Sentences299

to 21 years and 10 months, with the average age being 20 years and6 months on the day of testing.
Materials
As listed in Appendix D, 24 correct, 24 incorrect and 20 control
sentences (a total of 68 sentences) were prepared in the fourth experiment. Correct ‘Yes’ responses consisted of 24 potential sentences. These
were arranged in canonical order based on grammatical functions, thedative case marked subject (NP-ni) and the nominative case marked object(NP-ga) were then swapped to create sentences of scrambled order. For
example, a sentence Takashi-ni Girishaga-go kakeru-darooka (‘Can Takashi
write Greek?’) was altered to read Girishago-ga Takashi-ni kakeru-darooka.
These two sentences have the same meaning, so that a difference in syntactic structure can be directly compared in reaction times and error rates.
Again, a counterbalanced design was used to assign participants to different sentences. Two lists of 24 sentences (12 canonical and 12 scrambled)for correct ‘Yes’ responses were given to two groups of participants.
Twenty-four syntactically or semantically incorrect sentences wereused for correct ‘No’ responses to the task. Scrambled sentences were created on the basis of canonical sentences. For example, the phrase orderof the canonical sentence keshigomu-ni Masako-ga tetsudaeru-darooka (Can
Masako help an eraser?) was re-arranged to Masako-ga keshigomu-ni tetsudaeru-darooka. The counterbalanced design was also used for sentenceswith correct ‘No’ responses. Each list consisted of a total of 24 sentences(12 canonical and 12 scrambled) for correct ‘No’ responses.
In addition, the same 20 control sentences were added to each of thetwo lists. A total of 68 sentences in each list consisted of 24 correct (12canonical and 12 scrambled), 20 incorrect (10 canonical and 10 scrambled), and 20 control sentences.
ProcedureSame as Experiments 1–3.
Analysis and Results
Extremes among sentence correctness decision times (less than 400 ms
and longer than 4000 ms) were recorded as missing values. The means ofcorrect ‘Yes’ and ‘No’ reaction times and error rates for sentence correctness decisions are presented in Table V. Before performing the analysis,reaction times outside of 2.5 standard deviations at both the high and low
ranges were replaced by boundaries indicated by 2.5 standard deviations

Tamaoka et al.

300

Table V. Reaction Times and Error Rates for Potential Sentences

Response type
‘Yes’
Responses‘No’
Responses

Reaction time (ms)Error rate (%)

Sentence type

M

SD

M

SD

SOV
OSV
OSV-SOVSOVOSVOSV-SOV

1326
1542
216
1586
1602
16

299
366

4.17
29.86
25.69
5.90
7.99
2.08

7.37
24.93

349
318

6.72
8.33

from the individual means of participants in each category. Only stimulus
items of correct responses were used in the analyses of reaction times.
As in the previous experiments, ANOVAs with repeated measures incanonical and scrambled sentences were conducted with reaction times
and error rates for correct ‘Yes’ responses. Potential sentences in the fourthexperiment indicated scrambling effects in both reaction times (F1 (1, 23) =25.47, p < 0.001; F2 (1.23) = 13.61, p < 0.001) and error rates (F1 (1, 23) =30.54, p < 0.001; F2 (1.23) = 89.66, p < 0.001). The results suggested
that the canonical order deﬁned by grammatical functions was processed
faster and more accurately than the scrambled order (see Fig. 4). The
same ANOVAs were carried out for correct ‘No’ responses. Neither reaction times (F1 (1, 23) = 0.11, n.s., F2 (1, 24) = 0.02, n.s.) nor error
rates (F1 (1, 23) = 0.85, n.s., F2 (1.24) = 1.21, n.s.) showed signiﬁcantmain effects. Thus, no scrambling effects were observed for correct ‘No’
responses.
A very high error rate of 29.86% with a standard deviation of 24.93%
was observed for the processing of correct scrambled sentences. Numbersof correct responses for each participant are reported in Table VI. Threeparticipants properly responded to less than 3 of 12 scrambled potential
sentences. Since they were likely to properly judge other canonical andscrambled conditions for both ‘Yes’ and ‘No’ responses, some native Japanese speakers may rely on the information provided by case particles.
Discussion
The results of the fourth experiment indicated that the processing ofscrambled potential sentences of Fig. 4(ii) based on grammatical functions
required longer reaction times and resulted in higher error rates than the
canonical sentences depicted in Fig. 4(i). The results of scrambling effects
in the fourth experiment excluded case particles; therefore canonical orderPriority Information Used for the Processing of Japanese Sentences

301

Table VI. Number of Correctly-judged Potentcial Sentences by Participants‘Yes’ Response
Participants
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24

‘No’ Response

Canonical

Scrambled

Canonical

Scrambled

12
12
12
12
12
12
12
12
12
11
10
12
12
12
10
12
12
12
11
12
9
12
11
10

12
12
11
11
11
10
10
10
10
10
10
9
9
9
9
8
8
8
8
6
5
3
2
1

10
12
12
12
10
11
12
12
11
11
10
11
12
12
10
10
11
12
12
12
11
11
12
12

11
11
11
9
11
12
12
12
9
11
12
9
12
11
11
12
12
11
10
10
11
11
12
12

Note: A total of 12 sentences in each category.

is guided by grammatical functions which stand alone throughout the four
experiments. Native Japanese speakers must follow fundamental information provided by grammatical functions to decide whether or not a sentence is correct. The processing of scrambled sentences initiates a searchfor ‘gap’ to match the object NP-ga eigo-ga (‘English’) and the verb hanaseru-darooka (‘can speak’) as depicted in Fig. 4(ii). An error pattern among
participants indicated some peculiar trends; three participants continually
rejected scrambled correct potential sentences (see Table VI). If native Japanese speakers receive information from case particles, the nominative caseparticle –ga cannot be attached to the inanimate noun eigo (‘English’).
As shown in Table VI, three of the participants may follow case particles
rather than grammatical functions. Nevertheless, scrambling effects wereobserved including these data, so that this tendency does not alter theﬁndings of the fourth experiment.

Tamaoka et al.

302

EXPERIMENT 5: CAUSATIVE SENTENCES
The ﬁfth experiment further investigated whether or not case particle
ordering has any effect on sentence processing. This experiment differedfrom the fourth experiment in two important respects. First, the fourthexperiment used sentences with the dative and nominative case particles,
whereas the ﬁfth experiment employed sentences with the dative and accusative case particles. Different pairs of case particles might have different
effects on sentence processing. Second, the results of the fourth experimentsuggested that the effect of grammatical functions is more prominent thanthat of case particles. However, it has not yet been shown whether or notcase particles still have some effect albeit weaker than that of grammatical
functions. The ﬁfth experiment addressed this issue.
In the ﬁfth experiment, two kinds of verbs were used; transitive verbs
taking accusative object (i.e., accusative verbs) and transitive verbs taking
dative object (i.e., dative verbs). Examples are presented in Table VII.
When an accusative verb is used in the causative construction, thecausee (which corresponds to the subject argument in the simple transitive use) appears as an indirect object in the dative. On the other hand,in the causative construction with a dative verb, the causee appears as anindirect object in the accusative. The linear ordering of the indirect anddirect objects can be freely altered by scrambling. These possible orders
are shown in Table VIII.
Given the four types of causative sentences shown in Table VIII,
grammatical functions and case particles make different predictions
regarding canonical noun phrase order. According to the grammatical
function hierarchy speciﬁed in Table III, A1 and D1 are in canonicalorder, and A2 and D2 assume scrambled order. Thus, A1 and D1 should
be processed faster and more accurately than A2 and D2. In contrast,from the view point of the case particle hierarchy in Table III, A1 andD2 are canonical, and A2 and D1 are scrambled. Therefore, A1 and D2
should be processed faster and more accurately than A2 and D1. Finally,
if both grammatical functions and case particles affect sentence processing,Table VII. Simple Transitive Sentences with Accusative and Dative Verbs
Verb type

ExamplesAccusative verb

Deshi-ga
pupil-NOM

Dative verb

Deshi-ga
pupil-NOM

atorie-otukutta
atelier-ACC
built‘The pupil built the atelier.’
atorie-ni
komotta
atelier-DAT
stayed‘The pupil shut himself up in the atelier.’Junko-ga
deshi-oatorie-ni
Junko-NOM
pupil-DAT
atelier-ACC‘Junko made her pupil shut himself up in the atelier.’
Junko-gaatorie-ni
deshi-oJunko-NOM
atelier-ACC
pupil-DAT‘Junko made her pupil shut himself in the atelier.’

D1 (S.IO.DO.V/Nom-Acc-Dat-V)

D2 (S.DO.IO.V/Nom-Dat-Acc-V)

Junko-gaatorie-odeshi-niJunko-NOM
atelier-ACC
pupil-DAT‘Junko made her pupil build the atelier.’

A2 (S.DO.IO.V/Nom-Acc-Dat-V)

Dative Verb

Junko-gadeshi-niatorie-oJunko-NOM
pupil-DAT
atelier-ACC‘Junko made her pupil build the atelier.’

A1 (S.IO.DO.V/Nom-Dat-Acc-V)

Accusative Verb

ExamplesSentence type (Word order)

Verb Type

Table VIII. Causative Sentences with Accusative and Dative Verbs

komor-ase-ta
stay-CAUSE-PASTkomor-ase-ta
stay-CAUSE-PAST

tsukur-ase-ta
build-CAUSE-PAST

tsukur-ase-ta
build-CAUSE-PAST

Priority Information Used for the Processing of Japanese Sentences
303

304

Tamaoka et al.

A1 should be the easiest to comprehend (i.e., the shortest reaction time
and the lowest error rate), because it is the noun phrase order both hierarchies favor. A2 should be the hardest as neither grammatical functions norcase particles provide support for it. The reaction times and error rates of
D1 and D2 should be between those of A1 and those of A2, since grammatical functions and case particles make conﬂicting contributions in processing D1 and D2.
MethodParticipants
Thirty-two graduate and undergraduate students (18 females and 14
males, none of whom participated in the previous four experiments) at
Hiroshima University in Japan, all native speakers of Japanese, participated in the ﬁfth experiment. Ages ranged from 19 years and 0 months to
32 years and 3 months, with the average age being 22 years and 10 months
on the day of testing.
Materials
As listed in Appendix E, 32 sets of causative sentences for correct ‘Yes’
responses like those in Table VIII, and 32 sets of causative sentences
for correct ‘No’ responses (a total of 256 sentences) were prepared in
the ﬁfth experiment. Since three nouns used in both types of sentenceswith accusative and dative verbs, the only difference between two typesof sentences was the type of verbs. Thus, in order to make a directcomparison between sentences with accusative and dative verbs, these two
types of verbs were controlled by three variables of printed-frequency(utilizing the lexical corpus of Amano and Kondo, 2000), number of morae
and number of script symbols (i.e., kanji and hiragana) for both correct‘Yes’ and ‘No’ responses, respectively. For correct ‘Yes’ responses, t-tests
were conducted on these three variables between the two types of verbs.
A t-test showed that printed-frequencies (M = 21, 609, SD = 28, 180) for
accusative verbs did not differ from those (M = 15, 173, SD = 19, 595)
for dative verbs (t (62) = 1.06, n.s.). There was no difference between
the number of morae for accusative verbs (M = 5.78, SD = 1.01) andfor dative verbs (M = 5.53, SD = 0.88) (t (62) = 1.06, n.s.]. Likewise, thenumber of script symbols (M = 4.72, SD = 0.52) for accusative verbs did
not differ from those (M = 4.59, SD = 0.56) for dative verbs (t (62) = 0.92,
n.s.). For correct ‘No’ responses, the same t-tests were conducted onthese three variables between the two types of verbs. Printed-frequencies(M = 10, 341, SD = 11, 598) for accusative verbs did not differ from thosePriority Information Used for the Processing of Japanese Sentences305(M = 11, 405, SD = 21, 460) for dative verbs (t (62) = −0.25, n.s.). The
number of morae (M = 5.38, SD = 0.87) for accusative verbs did not
differ from those (M = 5.66, SD = 0.87) for dative verbs (t (62) = −1.30,
n.s.). Likewise, the number of script symbols (M = 4.59, SD = 0.56) for
accusative verbs did not differ from those (M = 4.78, SD = 0.66) for dative
verbs (t (62) = −1.23, n.s.). Four lists were created by distributing the test
items according to a Latin square design and intermixing 20 ﬁller sentencesin random order. Each participant saw only one list.
ProcedureSame as Experiments 1–4.
Analysis and Results
Extremes among sentence correctness decision times (less than 500 ms
and longer than 5000 ms) were recorded as missing values. The means ofcorrect ‘Yes’ reaction times and error rates for sentence correctness decisions
are presented in Table IX. Before performing the analysis, reaction times
outside of 2.5 standard deviations at both the high and low ranges were
replaced by boundaries indicated by 2.5 standard deviations from theindividual means of participants in each category. Only stimulus items ofcorrect responses were used in the analyses of reaction times.
For correct ‘Yes’ responses, 2 (accusative or dative verbs) × 2 (orders ofcase particles, nominative-dative-accusative or nominative-accusative-dative)
ANOVAs with repeated measures were conducted with reaction times anderror rates.
The result of reaction times did not show the signiﬁcant main effectof either accusative/dative verbs (F1 (1,31)= 0.461, n.s., F2 (1,31)= 1.299,
n.s.) or order of case particles (F1 (1,31)= 0.979, n.s., F2 (1,31)= 0.687,
n.s.). However, there was a signiﬁcant interaction in both variables
Table IX. Reaction Times and Error Rates for Causative Sentences
Reaction time (ms)
Verb type

Error rate (%)

Sentence type

M

SD

M

SD

Accusative Verb S.IO.DO.V (NOM-DAT-ACC-V)
S.DO.IO.V (NOM-ACC-DAT-V)
S.IO.DO.V-S.DO.IO.V
Dative Verb
S.IO.DO.V (NOM-ACC-DAT-V)
S.DO.IO.V (NOM-DAT-ACC-V)
S.IO.DO.V-S.DO.IO.V

2199
2386
187
2166
2351
185

497
559

10.55
23.44
12.8910.55
20.70
10.15

11.93
16.11

442
542

12.74
16.98

306

Tamaoka et al.

(F1 (1,31)= 15.517, p < 0.001, F2 (1,31)= 15.139, p < 0.001). As shown in
Table IX, the means of reaction times indicate effects in opposite
directions between accusative and dative verbs; the particle order of
nominative-dative-accusative seems to be faster to process than the orderof nominative-accusative-dative for accusative verbs, while this tendency
seems to be reversed for dative verbs. It was assumed that the signiﬁcantinteraction would be created by the reversal directions between accusativeand dative verbs. Thus, a one-way ANOVA repeated measures was conducted
for each type of verbs to examine the effect of case particle orders.
The result showed that sentences with the nominative-dative-accusative
order were processed faster than those with the nominative-accusativedative order (F1 (1, 31) = 6.196, p < 0.05, F2 (1, 31) = 8.841, p < 0.01) for
accusative verbs. As expected, this result was reversed in the dative
verbs that sentences with the nominative-accusative-dative order wasprocessed faster than those with the nominative-dative-accusative order(F1 (1, 31) = 8.836, p < 0.01, F2 (1, 31) = 4.155, p < 0.05) These analyses
conﬁrmed that accusative and dative verbs behave differently in theprocessing of sentences regarding the order of case particles.
As for error rates, the same ANOVA analysis was conducted. As
in the case of reaction times, the result of error rates also showed nosigniﬁcant main effect of either accusative/dative verbs (F1 (1,31)= 0.725,
n.s., F2 (1,31)= 0.104, n.s.) or order of case particles (F1 (1,31)= 0.309,
n.s., F2 (1, 31) = 0.274, n.s.) but, there was a signiﬁcant interaction inboth variables (F1 (1,31)= 29.524, p < 0.001, F2 (1, 31) = 35.791, p < 0.001).
The trend of error rates also seems to display the same pattern
as reaction times. Thus, a one-way ANOVA repeated measures was
conducted for each type of verb. The result showed that sentences with
the nominative-dative-accusative order were processed more accurately
than those with the nominative-accusative-dative order for accusative
verbs (F1 (1,31) = 17.303, p < 0.001, F2 (1, 31) = 11.597, p < 0.01). As
expected, this result was reversed in the case of dative verbs;
sentences with the nominative-accusative-dative order were processedmore accurately than those with the nominative-dative-accusative order(F1 (1,31) = 8.986, p < 0.01, F2 (1,31) = 15.274, p < 0.001). Consequently,
error rates also depicted the same pattern as shown in reaction times.

Discussion
The results of the ﬁfth experiment showed that the processing ofscrambled causative sentences based on grammatical functions (A2 and D2)
required longer reaction times and resulted in higher error rates thanPriority Information Used for the Processing of Japanese Sentences307

the canonical sentences (A1 and D1) regardless of the order of caseparticles. This suggests that grammatical functions play a prominent role insentence processing, and that strict linear ordering of case particles has noobservable effect on the speed and accuracy in sentence comprehension.
GENERAL DISCUSSION
As outlined in Table X, the aim of the present study was two-fold: (1)to investigate scrambling effects on the processing of Japanese sentences;and (2) to identify the priority of information among thematic roles, caseparticles and grammatical functions used by native Japanese speakers insentence processing. The following two sections discuss the results based
upon the ﬁve experiments.
Scrambling Effects and Syntactic Structure
The ﬁrst and second experiments indicated that reaction times forcorrect sentence decisions were signiﬁcantly prolonged for scrambled active
sentences. In addition, more errors were made with scrambled thancanonical sentences. Thus, these two experiments supported scrambling
effects previously found by Chujo (1983) and Mazuka et al. (2002). As
discussed in the introduction, when an accusative noun phrase was placedin the sentence-initial position and followed by a nominative noun phrase,
native Japanese speakers began searching for a ‘gap’ to match up withthe verb. Active sentences with ditransitive verbs (scrambling effects of
604 ms) require a longer decision-making time for scrambled sentences
than those with transitive verbs (scrambling effects of 223 ms). Since theconﬁgurational structure for ditransitive verbs as depicted in Fig. 2 haslonger distances than transitive verbs in Fig. 1, a ‘gap’ for ditransitive verbs
from the sentence-initial position of NP-o has a longer distance than a ‘gap’
for transitive verbs. The distance difference or longer-distance scrambling(Nemoto, 1999) may have resulted in a greater disparity in the processing
speed for ditransitive verbs (i.e., 381 ms longer than the active sentenceswith transitive verbs). In addition to the great difference between thescrambling effects of transitive and ditransitive verbs in active sentences, thethird and fourth experiments showed a similar degree of scrambling effects
to the ﬁrst experiment; 201 ms for passive sentences in the third experimentand 216 ms for potential sentences in the fourth experiment. Although typesof sentences differ among the ﬁrst, third and fourth experiments, all objects
had the same distance to verbs. Therefore, it seems that the longer-distancescrambling between an object and a verb appeared to determine the degreeof scrambling effects.

Experiment 1
Experiment 2
Experiment 3
Experiment 4
Experiment 5

Scrambling effects

Active sentences with transitive verbs
Active sentences with ditransitive verbs
Passive sentences with transitive verbs
Potential sentences
Causative Sentences

Sentence types

Note: X refers to a possible explanation for the sentence processing.

Priority Information

Experiment #Purpose of experiments
X
X
Excluded

Thematic roles
X
X
X
Excluded
ExcludedCase particles
X
X
X
X
X

Grammatical functions

Table X. Possible Explanations for Scrambling Effects through Five Experiments

308
Tamaoka et al.

Priority Information Used for the Processing of Japanese Sentences309

The results of the ﬁrst and second experiments also provide evidence
for syntactic structure which appropriately explains the construction ofJapanese sentences. Tamaoka et al. (2003) depicted three possible sentence
structures. The ﬁrst structure is the ‘non-conﬁgurational’ syntactic structurenoun phrase order in Japanese does not alter the fundamental meaning,leading a group of linguists (e.g., Farmar, 1984; Hale, 1980, 1981) toclaim that it is non-conﬁgurational or ‘ﬂat’ in structure. This structuralmodel predicts no differences in the processing of canonical and scrambled
noun phrase order. The second structure is called a ‘conﬁgurational’
syntactic structure. Several linguists (e.g., Hoji, 1985; Miyagawa, 1989;
Saito, 1985; Saito and Hoji, 1983 for Japanese; Mahajan, 1990; Müller
and Wolfgang, 1994; Webelhuth, 1989 for other languages) claim that an
instance of phrasal movement results in free noun phrase order phenomena.
This structural model predicts to have a difference in speed and accuracy
between canonical and scrambled order. The ﬁndings of the ﬁrst andsecond experiments support this structure. The third structure is either a‘conﬁgurational structure without movement’ or a ‘base-generated structure’.
Tonoike (1997) argues that certain instances of Japanese scrambled phrases
and sentences are base-generated in their surface positions. Fukui (1989)
makes a similar point that scrambling is a ‘substitution’ into a base-generated
position. This structure predicts to result in equal processing speeds, butdiffers in accuracy between canonical and scrambled order. The ﬁndings of
the ﬁrst and second experiments indicated differences in speed and accuracy
between canonical and scrambled sentences, so that the second candidateof the conﬁgurational structure seems to explain the results properly.
Therefore, the ﬁrst and second experiments supported the conﬁgurational
structure in which the gap-ﬁlling parsing operation functions for scrambled
sentences.
Finally the existence of the scrambling effects in the ﬁrst and thesecond experiments of the present study on the one hand and the lack ofsuch effects in Nakayama (1995) and Yamashita (1997) on the other, show
important differences in experimental methodologies employed in thesestudies. Nakayama and Yamashita used self-paced reading paradigm, that
required subjects to press a key when they ﬁnished reading a part of sentence
presented in phrase-by-phrase fashion. Self-paced reading is usually regarded
as a very informative measure because it provides information about theintermediate steps of sentence comprehension. At the same time the method
is a less sensitive measure when compared to the sentence-ﬁnal judgment
method used in our experiment. This is because participants are likely to pay
more attention to judgment components and are likely to create their own
reading rhythm during the experiment unrelated to their natural reading pace.
The self-paced reading method is thus successful in capturing scrambling

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effects only if a scrambled phrase is moved far away and the effects becomes
sufﬁciently large as reported by Miyamoto and Takahashi (2004). Given
these considerations the sentence-ﬁnal decision method used in this paper
is an effective method that gives us valuable information about scrambling
effects, even if it does not tell us the exact time line of sentence processing.
Priority Information for Identifying Canonical Order
Active sentences of the ﬁrst and second experiments supported all threepossible information cues of thematic roles, case particles and grammatical
functions for identifying canonical noun phrase order. Thus, the present
study further investigated priority information in the third, fourth and ﬁfth
experiments. In the passive sentences, thematic roles and case markers offerdifferent information regarding canonical order. As depicted in Fig. 3,
thematic roles provide information that the agent NP-ni follows the theme
NP-ga, while case particles show the reverse pattern that a noun with
the nominative case particle –ga precedes a noun with the dative caseparticle –ni. The third experiment proved scrambling effects in the direction
indicated by case particles. Thus, thematic roles were excluded from thepriority of information, while case particles and grammatical functions
remained candidates.
The fourth and ﬁfth experiments compared the effects of case particles
and grammatical functions on sentence processing. In potential sentences,case particles and grammatical functions provide different information
concerning canonical order. In potential sentences the dative case particle–ni is assigned to syntactic properties of the subject (Fukui, 1988, 1995;
Shibatani, 1978). Thus, grammatical functions indicate the canonical orderthat a subject with –ni comes before an object with –ga. In contrast,case particles provide information that the noun phrase particle-marked–ga precedes the noun phrase particle-marked –ni. The fourth experiment
revealed the scrambling effects on potential sentences which were orderedon the basis of grammatical functions as shown in Fig. 4. Using four typesof causative sentences, the ﬁfth experiment further investigated the possible
effect of case particles on sentence processing. The ﬁfth experiment differedfrom the fourth experiment in two respects: (i) it examined the combinationof the dative and accusative case particles rather than the dative andnominative particles, and (ii) its experimental design made it possible todirectly compare the effects of the two possible case particle orders (i.e.,
dative-accusative vs. accusative-dative) in addition to compare the effect ofcase particle ordering and that of grammatical functions. The result of theﬁfth experiment clearly showed that linear ordering of the dative andaccusative case particles does not affect the speed and accuracy in sentencePriority Information Used for the Processing of Japanese Sentences

311

comprehension. Therefore, case particles were excluded from the list ofpriority information, leaving only the possibility of grammatical functions.
Consequently, the scrambling effects found in the present study indicatedthat neither thematic roles nor case particles can provide fully satisfactory
information for canonical phrase order, and that only grammatical functions
offer plausible information in all active, passive and potential sentences. An
important issue which remained unexamined in this paper was exactly when
gap-ﬁlling parsing was initiated. Since grammatical function information isusually dependent on the type of predicates, native speakers sometime
cannot determine the correct grammatical function of noun phrases by theend of sentence in a head-ﬁnal language like Japanese. This suggests thatat least some part of the idea of the wait-and-see model must be truein the sentence processing mechanism of head-ﬁnal languages. Since thesentence-ﬁnal judgment paradigm used in this paper does not give us
decisive information about the timing of gap-ﬁlling operation, we leave thispossibility as an avenue for future research.

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312

APPENDIX A. The Active Sentences with Transitive Verbs for Experiment 1
Canonical sentences
Items for Correct ‘Yes’ Responses

Scrambled sentences

Priority Information Used for the Processing of Japanese Sentences
APPENDIX A. Continued
Canonical sentences

Scrambled sentences313

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314
APPENDIX A. Continued
Canonical sentences

Scrambled sentences

Priority Information Used for the Processing of Japanese Sentences
APPENDIX A. Continued
Canonical sentences

Scrambled sentences

315

Items for Correct ‘Yes’ Responses

Canonical sentences

Scrambled sentences

APPENDIX B. The Active Sentences with Ditransitive Verbs for Experiment 2
316
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Priority Information Used for the Processing of Japanese Sentences317

Items for Correct ‘Yes’ Responses

Canonical sentences

Scrambled sentences

APPENDIX C. The Passive Sentences with Transitive Verbs for Experiment 3
318
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Priority Information Used for the Processing of Japanese Sentences319

Canonical sentences

Scrambled sentences

APPENDIX C. Continued
320
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Priority Information Used for the Processing of Japanese Sentences321

Items for Correct ‘Yes’ Responses

Canonical sentences

Scrambled sentences

APPENDIX D. The potential sentences for Experiment 4322
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Priority Information Used for the Processing of Japanese Sentences323

Canonical sentences

APPENDIX D. Continued
Scrambled sentences

324
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Items for Correct ‘Yes’ Responses for Sentences with Accusative Verbs

Canonical sentences

Scrambled sentences

APPENDIX E. The causative sentences for Experiment 5

Priority Information Used for the Processing of Japanese Sentences
325

Canonical sentences

Scrambled sentences

APPENDIX E. Continued
326
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Priority Information Used for the Processing of Japanese Sentences327

Canonical sentences

Scrambled sentences

APPENDIX E. Continued
328
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Priority Information Used for the Processing of Japanese Sentences329

Canonical sentences

Scrambled sentences

APPENDIX E. Continued
330
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Priority Information Used for the Processing of Japanese Sentences

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