Behavioral and neural evidence on the processing of ambiguous adjective-noun dependencies in Korean sentence comprehension

Brain and Language 188 (2019) 28–41

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Behavioral and neural evidence on the processing of ambiguous adjectivenoun dependencies in Korean sentence comprehension Yunju Nama,c, Upyong Hongb,c,

T

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a

KU Institute for Communication Studies, Konkuk University, Seoul 5029, Republic of Korea Dept. of Media and Communication, Konkuk Univeirsity, Seoul 5029, Republic of Korea c Brain and Cognition Research Center, Konkuk University, Seoul 5029, Republic of Korea b

ARTICLE INFO

ABSTRACT

Keywords: Adjectives Nouns Semantic Congruence Ambiguity resolution Long distance dependency ERP N400 Korean

In Korean, it is allowed for an adjective to modify a distant noun that appears after an intervening relative clause instead of an adjacent noun. The current study investigated the time course of syntactic and semantic integration between an adjective (A) and an adjacent noun (N1) and/or a distant noun (N2) during on-line reading comprehension of Korean sentences. Semantic congruence between adjectives and nouns were manipulated, such that A was congruent with both N1 and N2, either with N1 or N2, or with none of N1/N2. The reading times and ERPs to critical words revealed that under A-N1 semantic incongruence, not the processing load of N1, but those of the relative clause verb and N2 which is semantically incongruent with A increased. These results imply that the semantic incongruence suppressed the A-N1 integration until the relative clause verb occurred, and the processor immediately attempted the A-N2 integration for a way out from the ultimate processing breakdown even before the occurrence of the main verb.

1. Introduction An important topic of contention in research about on-line sentence comprehension is the precise point at which the processor encounters ambiguities and the manner in which disambiguation proceeds, succeeds, or fails. In particular, specifying the time course of the history of successful or unsuccessful disambiguation procedures will allow complete on-line sentence comprehension in head-final languages, in which almost every incoming word is compatible with multiple ways of phrase structure building, to be determined (Inoue & Fodor, 1995; Kwon, 2008). This is why a universal theory of sentence comprehension is hardly conceivable, without clearer understanding of the disambiguation mechanism in head-final languages. In this regard, psycholinguistic approaches to analyze the processing strategy of head-final languages can be classified either in terms of the timing or the manner of ambiguity resolution. One well known approach is “head-driven parsing” (Pritchett, 1991, 1992), which assumed that the integration between noun phrases (NPs) is delayed until their licensing head appears. In line with “the projection principle,” which holds that each level of syntactic representation is a uniform projection of the lexical properties of heads (Pritchett, 1991), the headdriven parsing model suggests that a phrasal node cannot be projected until its head occurs. Correspondingly, all NPs would remain

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unattached until the sentence-final verb position in head-final languages. This implies that the processor might not, or even cannot, choose a particular phrase structure at the position of syntactic ambiguity, if the clause/sentence-final verb is missing. In other words, the head-driven parsing might be tolerant to the syntactic ambiguities in head-final languages, at least temporarily. However, disambiguation should be initiated no later than the occurrence of the verb, at which all of the preceding sentence constituents are somehow organized into a verb phrase (VP). The incremental parsing model, in contrast, assumes that the processor does not necessarily wait until a particular lexical category (e.g., verb) occurs, but rather, constructs a sequence of partial phrase structures at every possible position (Bader & Lasser, 1994; Kamide & Mitchell, 1999; Miyamoto, Gibson, Pearlmutter, Aikawa, & Miyagawa, 1999). Moreover, the processor’s strategy of incremental integration is taken to hold not only for the relatively well predicted post-verbal sentence constituents in head-initial languages but also for much less predictable pre-verbal sentence constituents in head-final languages (Inoue & Fodor, 1995). In this regard, there should be no delay of the integration between NPs, even prior to the occurrence of the verb in head-final languages. Correspondingly, immediate decisions would be made at every region of syntactic ambiguities, irrespective of whether such a choice would turn out to be correct or not. If the adopted phrase

Corresponding author at: Department of Media and Communication, Konkuk University, Seoul 5029, Republic of Korea. E-mail address: [email protected] (U. Hong).

https://doi.org/10.1016/j.bandl.2018.11.004 Received 11 April 2017; Received in revised form 24 October 2018; Accepted 21 November 2018 0093-934X/ © 2018 Elsevier Inc. All rights reserved.

Brain and Language 188 (2019) 28–41

Y. Nam, U. Hong

structure turns out to be false, a reanalysis should follow (Frazier & Fodor, 1978). The current study aimed to provide new evidence on disambiguation procedures in on-line sentence comprehension of a head-final language, i.e., Korean, based on which the explanatory power of headdriven vs. incremental parsing model can be critically evaluated. In particular, we focused on the fact that the Adjective(A)-Noun(N) string in Korean is ambiguous in the sense that the A could modify either the adjacent N in a simple NP construction such as ‘[NP A N]’, or another N in a more complex construction like ‘A [RC N …] N’. Note that the latter construction included an embedded relative clause beginning with the first N and headed by the second N, which is frequently observed in head-final languages (see Section 2). Further, also note that, in such a construction, adjective only modifies the long-distance noun, but not the adjacent one. Therefore, the processor might well choose the option of ‘embedded relative clause’ at the position of first N, especially if an A-N semantic incongruence would be detected. Contrary to this scenario, which accords with the incremental processing model, the processor might wait and see until the occurrence of a verb in line with the head-driven parsing model, without having integrated the involved A and N. Of course, the possibility of building a simple NP like [NP A N] neglecting the semantic incongruence could not be ruled out as well (cf. Nam & Hong, 2016). Crucially, the processor of Korean might well consider the longdistance A-N integration given adjacent A-N semantic incongruence, if sufficient cues are provided, highlighting the possibility of separating A from the adjacent N by an intervening relative clause. Although it is doubtless that the grammar of the Korean language provides a way out from a semantic conflict between adjacent A and N already at the N position, whether, or in what conditions/manners, the processor takes advantage of such an option is an empirical question. Clarifying this question will contribute to the more detailed characterization of the disambiguation mechanism in head-final languages on the one hand, and to a critical evaluation of competing models of sentence comprehension on the other.

semantically congruent either only with the adjacent N1, or with the distant N2. Notice that the words used in (2) are exactly of the same categories, in the identical order, to those in (1).

In (2a), the adjective ‘maeun (spicy)’ is semantically congruent with N1 ‘gochu (chili)’, but not with N2 ‘jaru (sack)’. Thus, the ambiguity illustrated in (1) could be resolved at N2, resulting in the representation of the structure (2a′). In contrast, the adjective ‘nalgeun (worn)’ in (2b) is semantically compatible with N2 ‘jaru (sack)’, butr not with N1 ‘gochu (chili)’. Hence, the corresponding syntactic representation should be (2b′), in which the adjective is pushed outside the relative clause and modifies the distant N2. Since the correct representations could be chosen at N2 prior to the end of the sentence, (2a) and (2b) are taken to be only locally ambiguous. Bearing in mind the short vs. long distance A-N dependencies described above, an interesting issue to be addressed, with respect to online sentence comprehension, is the kind of processing efforts that are required at each point of unfolding phrase structure. Let us consider (3) in this regard.

2. Adjacent vs. distant adjective-noun dependency in Korean: from ambiguities to resolutions

In (3a), which has no semantic conflict between A and N, the processor would most probably integrate the adjective ‘maeun (spicy)’ and ‘gochu (chili)’ incrementally at the N position. In (3b), however, an incremental A-N integration purely based on the syntactic category information is in contradiction with the A-N semantic incongruence. Therefore, a certain amount of processing load, due to the involved semantic violation, is expected at the N position, if the processor immediately builds an NP like ‘[NP A N]’. Alternatively, if the processor would build another phrase structure to avoid the A-N semantic conflict, e.g., ‘A [RC N…]’, or would not build a fixed phrase structure including A and N at all, no effect of A-N semantic incongruence is expected at the N. In short, the amount of processing load at the N of (3b) would depend on the kind of parsing strategy that is applied at that region. Regardless of the processor’s choice at the N of (3b), there could be a second trial to integrate the A with an additional N. The time course of such additional processing efforts whereby the secondary integration could succeed in (4a), but not in (4b) need to be specified. If the longdistance A-N2 integration is attempted, clear evidence of an (in)congruence effect should be visible at N2, i.e., the amount of processing load at the N2 of (4b) should be greater than at (4a).

In Korean, a sentence like (1a), which is seen below, is ambiguous since the attributive adjective ‘maeun (spicy)’, might either modify the adjacent noun (N1, henceforth), i.e., ‘gochu (chili)’, or another distant noun (N2, henceforth) such as ‘ramyeon (noodle)’. The ambiguity is due to a relative clause [maeun gochu-lul neoh-eun] that is embedded in the sentence. That is, the accusative noun ‘ramyeon (noodle)-ul’, which is the object of the transitive verb ‘ssot (spill)-at-da’, is at the same time the head of the relative clause ending with the relativized verb ‘neoh (put in)-eun’. If the adjective occurs within this relative clause, as illustrated in (1b), it modifies the adjacent N1. In contrast, as can be seen from (1c), if it is outside of that relative clause, the adjective should be taken to modify the distant head of the relative clause N2.

Contrary to example (1), which is globally ambiguous in the sense that there is no way of disambiguation even at the end of the sentence, examples like (2) are only locally ambiguous since the adjective is 29

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Y. Nam, U. Hong

Further, note that for long-distance A-N2 integration to be available, an embedded relative clause, which does not include the adjective within itself, should be completed at some point of unfolding phrase structure. This additional requirement would be easily met if the processor has already constructed the partial relative clause ‘A [RC N…]’ at the N1 region. A reanalysis, however, would become necessary if the processor has constructed a simple NP like ‘[NP A N]’. This implies that the type or amount of processing load measured at the region of relativized verb (Vr, henceforth) (‘neoh-eun (put-in)’) is also relevant to uncovering the mechanism of the adjacent and/or long-distance A-N integration. The present study aimed to explore the time course of the on-line processing of Korean sentences, which included ambiguities, in terms of A-N dependency discussed so far. For this purpose, the reading time and ERP responses of Korean speakers were recorded while they read sentences, which included adjacent and/or long-distance A-N semantic (in) congruence. Comparing the reading time and ERP responses to N1 in adjacent incongruence (AI) conditions (i.e., adjacent incongruence + distant congruence [AIDC] and adjacent incongruence + distant incongruence [AIDI]) with that of adjacent congruence (AC) conditions (i.e., adjacent congruence + distant congruence [ACDC] and adjacent congruence + distant incongruence [ACDI]), will enable us to elucidate the parsing strategy Korean speakers adopt. An increased processing load in AI conditions, compared to AC conditions, would imply the construction of [NP A N] at N1, while the absence of such an increase would suggest the construction of an alternative phrase structure, such as A [RC N…], or no fixed phrase structure including A and N yet. In the latter two cases, the comparison of results to N2 between AIDC and AIDI conditions would be critical, since successful long-distance A-N integration is only possible in AIDC, but not in AIDI. However, the time course of combining the dangling adjective with the incoming head noun would vary, depending on which option the processor has adopted, i.e. the embedded relative clause, or no fixed phrase structure including A-N integration. In this regard, analyses of the reading time and ERP responses to the embedded and main verbs would be illuminating. In sum, the experiment paradigm described above will enable us to describe the processing of ambiguous A-N dependency in Korean and contribute to a more detailed characterization of the disambiguation mechanism in head-final languages in general.

Two adjacent incongruence conditions were constructed based on the ACDC and ACDI conditions. For AIDC condition, we used another adjective (e.g., nalgeun ‘worn’) which was not congruent with the N1 (e.g., gochu ‘chili’) but congruent with the N2 (e.g., jaru ‘sack’) and the other components were same as ACDI. The AIDI condition was constructed based on the ACDC condition. Namely, for AIDI condition, we used an adjective (e.g., nalgeun ‘worn’) which was neither congruent with N1 (e.g., gochu ‘chili’) nor with N2 (e.g., ramyeon ‘noodle’). In addition to the List A, which contained 24 experimental sentences constructed in the manner described above, we made List B including the other 24 experimental sentences to avoid lexical differences of adjectives. That is, the adjectives used in the adjacent congruence conditions (ADCD & ACDI) of List A were used for the adjacent incongruent conditions (AIDC & AIDI) in List B and the adjectives used in the adjacent incongruent condition of List A were used for the adjacent congruence conditions of List B. Each sentence began with a personal name, which is frequently used in Korea and ended with a transitive verb that required an animate agent subject and an inanimate theme object. Additionally, an adverb was inserted between the N2 and the main verb (Vm) concerning the overwrapped effect between the distant noun and the Vm. The number of syllables in each lexical item was held constant at two to four syllables. Beside the 192 target sentences (48 in each of four conditions), we added 176 filler sentences that had double nominative construction, including an embedded clause such as “subject noun (in the main clause) + subject noun (in the relative clause) + relativized verb + object noun + main verb”, without semantic anomalies. A total of 368 sentences were divided into four blocks, where each block included 48 target sentences (12 × 4 conditions) and 44 fillers. Participants were exposed to all blocks, which were presented visually in a pseudo-randomized order. No more than two sentences from the same condition were presented successively in order to prevent a repetition or syntactic priming effect (Hahne & Friederici, 2002; Zhang, Jiang, Saalbach, & Zhou, 2011). 3.3. Procedure Self-paced reading was conducted in a moving-window fashion with incremental judgment. The secondary judgment task was applied in order to increase the sensitivity of the methodology to subtle semantic acceptability, which might not be observed in a straight reading paradigm (Mauner, Tanenhaus, & Carlson, 1995). Before seeing the stimulus sentences, participants saw a row of dashes corresponding to all of the words of each sentence on a computer monitor. When participants pressed the ‘Yes’ key (i.e., the ‘B’ key of the keyboard), the first region was replaced by words. The participants were required to press the ‘Yes’ key again to see the next region. When the next region was switched into the segment, the preceding region was reverted to dashes. Participants kept pressing the ‘Yes’ key to read subsequent regions until they had judged the corresponding sentence did not make sense, at which point they pressed the ‘No’ key (i.e., the ‘N’ key of the keyboard). As soon as participants pressed the ‘No’ key, the current trial was terminated and the next trial was initiated. The ‘Yes’ reading time and percentage of ‘No’ responses were analyzed for each region respectively. Before the experiment started, participants were provided with instructions for the task and a practice with five semantically congruent and five incongruent sentences, so that they could familiarize themselves with the task and response keys.

3. Experiment 1: Self-paced reading with secondary judgment 3.1. Participants A total of 62 native speakers of Korean, with normal or corrected-tonormal vision, took part in the on-line reading study. They were undergraduate students at Konkuk University in Seoul, S. Korea. All participants joined the experiment voluntarily and received $10 for participation. 3.2. Materials All sentences were constructed with the following composition: “subject noun + adjective + object noun 1 (N1) + relativized verb + object noun 2 (N2) + adverb + main verb.” The semantic congruence between an adjective and an N1 and/or an N2 were manipulated as described in Table 1. For the ACDC condition, we used an adjective that was semantically congruent with N1 and N2 simultaneously. Thus, there was no incongruence between the adjective (e.g., maeun ‘spicy’) and both the adjacent noun (e.g., gochu ‘chili’) and distant noun (e.g., ramyeon ‘noodle’) in ACDC condition. In the ACDI condition, we replaced the distant noun with semantically inappropriate ones (e.g., jaru ‘sack’) with the preceding adjectives (e.g., maeun ‘spicy’). However, since we used the appropriate main verb (e.g., yeomyeotda ‘tie’) in the sentence final position, there was no semantic violation in ACDI conditions as well.

3.4. Analysis and results The results of the self-paced reading experiment were analyzed using two dependent variables, i.e., the percentage of ‘No’ judgments for each segment and the reading times for each region before the participants pressed ‘Yes’. The percentage of ‘No’ responses were used 30

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Table 1 Experiment conditions and example sentences. List A. Adjacent

Distant

Condition

Sub.

Adj.

N1

Vr

N2

Adv.

Vm

O

O

ACDC

Gitae-ga Gitae-nom.

maeun spicy

gochu-lul chili-acc.

neoh-eun put in-rel.

ramyeon-ul noodle-acc.

silswulo accidentally

ssot-at-da. spill-past-dcl.

O

X

ACDI

Sungho-ga Sungho-nom.

maeun spicy

gochu-lul chili-acc.

neoh-eun put in-rel.

jaru-lul sack-acc.

tantanhi tightly

yeomy-eot-da tie-past-decl.

X

O

AIDC

Juhee-ga Juhee-nom.

nalgeun worn

gochu-lul chili-acc.

neoh-eun put in-rel.

jaru-lul sack-acc.

tantanhi tightly

yeomy-eot-da tie-past-decl.

X

X

AIDI

Yongsu-ga Youngsu-nom.

nalgeun worn

gochu-lul chili-acc.

neoh-eun put in-rel.

ramyeon -ul noodle-acc.

silswulo accidentally

ssot-at-da spill-past-decl.

List B. added for controlling the lexical differences of adjectives across conditions Adjacent

Distant

Condition

Sub.

Adj.

N1

Vr

N2

Adv.

Vm

O

O

ACDC

Minsu-ga Minsu-nom.

nalgeun worn

panci-lul ring-acc.

ppathuli-n drop-rel.

thong-ul basket-acc.

kuphi hurriedly

twi-cyess-ta fumble-past-decl.

O

X

ACDI

Yunjae-ga Yunjae-nom.

nalgeun worn

panci-lul ring-acc.

ppathuli-n drop-rel.

ccikay-lul stew-acc.

cayppalli quickly

twi-cek-yess-ta stir-past-decl.

X

O

AIDC

Hyesoo-ga Hyesoo-nom.

maeun spicy

panci-lul ring-acc.

ppathuli-n drop-rel.

ccikay-lul stew-acc.

tantanhi quickly

twi-cek-yess-ta stir-past-decl.

X

X

AIDI

Yunji-ga Yunji-nom.

maeun spicy

panci-lul ring-acc.

ppathuli-n drop-rel.

thong-ul basket-acc.

kuphi hurriedly

twi-cyess-ta fumble-past-decl.

Note. Critical words for electroencephalogram recording are underlined. O: semantically congruent, X: semantically incongruent.

Fig. 1. The percentage of adjusted ‘No’ responses at critical regions (N1 to Vm) (a) The percentage of adjusted ‘No’ rejection (b) The percentage of accumulative ‘No’ rejection.

to estimate how tolerant the participants were in integrating words into sentences at a single critical region. ‘Yes’ reading time indicated more difficulty in processing the sentence. Data from three participants were excluded since they rejected more than 80% of sentences or had a reading time longer than 5000 ms for one word. Consequently, a total of 62 participants were included in the final analysis. Statistical analysis was performed using repeated measures analysis of variance (ANOVA), with adjacent congruence and distance congruence as variables.

for each participant and they were depicted in Fig. 1. The statistical analysis was performed with the adjusted ‘No’ rejection percentage data1 as described in Table 2. The main effects of adjacent congruence were observed From N1 to the Vm region consistently, indicating that adjacent A-N1 incongruent sentences were rejected more than adjacent A-N1 congruent sentences from N1 to sentence final region (as summarized in Table 2). Noticeably, the main effects of the distant congruence were significant at N2 (F1(1,61) = 3.960, p < 0.05; F2(1,43) = 5.323, p < 0.05), adverb (F1(1,61) = 6.518, p < 0.05; F2(1,43) = 3.190, 0.05 < p < 0.1), and Vm position (F1(1,61) = 14.724, p < 0.001; F2(1,43) = 7.995, p < 0.01), implying that distant incongruent sentences in the ACDI and AIDI conditions were rejected more than distant congruent sentences in the ACDC and AIDC conditions, at these regions. In addition, the interactions between adjacent and distant congruence were significant at adverb (F1(1,61) = 4.014, p < 0.05) and Vm region

3.4.1. ‘No’ judgments For a brief overview of ‘No’ rejections across the conditions, we tabulated the “Adjusted No” judgments at each region of a sentence using the procedure introduced in Boland, Tanenhaus, and Garnsey (1990). The adjusted ‘No’ percentages (Fig. 1(a)) were calculated by dividing the number of ‘No’ judgments at a critical region by the number of remaining opportunities that a participant had for responding ‘No’ in that sentence. The mean adjusted and accumulative ‘No’ percentages were then computed according to condition and region

1 The adjusted ‘No’ response percentage was not statistically different from the accumulative ‘No’ percentage.

31

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Table 2 The summary of statistical analysis for the adjusted ‘No’ rejections. N1

Vr

N2 **

Adv. **

Vm

Adjacent congruence

F1(1,61) = 52.673 F2(1,43) = 86.702**

F1(1,61) = 152.938 F2(1,43) = 144.176**

F1(1,61) = 45.700 F2(1,43) = 28.897**

F1(1,61) = 32.483 F2(1,43) = 22.790**

F1(1,61) = 32.232** F2(1,43) = 1.083

Distant congruence

F1(1,61) = 0.248 F2(1,43) = 0.218

F1(1,61) = 0.537 F2(1,43) = 0.145

F1(1,61) = 3.960* F2(1,43) = 5.323*

F1(1,61) = 6.518* F2(1,43) = 3.190^

F1(1,61) = 14.724** F2(1,43) = 7.995**

Adjacent × Distant

F1(1,61) = 0.202 F2(1,43) = 0.240

F1(1,61) = 0.947 F2(1,43) = 0.511

F1(1,61) = 1.307 F2(1,43) = 0.421

F1(1,61) = 4.014* F2(1,43) = 2.128

F1(1,61) = 4.269* F2(1,43) = 0.095

– –

– –

– –

F1(1,61) = 0.958 F1(1,61) = 5.512*

F1(1,61) = 5.660* F1(1,61) = 9.940**

ACDC vs. ACDI AIDC vs. AIDI

**

**

p < 0.01 **, p < 0.05 *, and 0.05 < p^ < 0.1 (F1: Participant analysis; F2: Item analysis). ACDC: adjacent congruence and distant congruence; ACDI: adjacent congruence and distant incongruence; AIDC: adjacent incongruence and distant congruence; AIDI: adjacent incongruence and distant incongruence. N1: first (adjacent) noun; Vr: relativized verb; N2: secondary (distant) noun; Adv.: Adverb; Vm: main verb.

(F1(1,61) = 4.269, p < 0.05) in participant analysis. Further analysis revealed that the ‘No’ rejection percentage in the AIDI condition was higher than in the AIDC, at the adverb (AIDC 9.7% vs. AIDI 18.4%; F1(1,61) = 5.512, p < 0.05) and Vm (AIDC 17.5% vs. AIDI 32.1%; F1(1,61) = 9.940, p < 0.01). 3.4.2. ‘Yes’ response time Before we analyzed the ‘Yes’ reading time of target words, we removed extreme reading time data (over 3000 ms) to avoid magnifying estimation of the data. Then, reading times above or below 2.5 × SD (standard deviation) of a participant’s mean reading time, at each region, were replaced with ‘mean ± 2.5 × SD’ boundary value. As described in Fig. 2, the ‘Yes’ reading time in adjacent incongruent conditions were highly increased at the Vr, N2, Vm region. Statistical analysis with adjacent and distant congruence factors revealed a significant main effect of adjacent congruence at the Vr region (F1(1,61) = 47.824, p < 0.001; F2(1,43) = 69.058, p < 0.001) and main effect of adjacent congruence at the Vm region in participant analysis (F1(1,61) = 4.583, p < 0.05). The main effect of the distant congruence was marginally significant at Vm region (F1(1,61) = 3.657, 0.05 < p < 0.1). There were no interactions between the adjacent and distant congruence in whole regions. In spite of the longer reading time observed in AIDC (770 ms) compared to AIDI (729 ms) condition at the N2 region, this difference was not statistically significant both in participant and item analysis (see Table 3).

Fig. 2. The ‘Yes’ response times (RTs; in ms) of every single word across the conditions.

presentation (RSVP) way with a stimulus onset asynchrony and interstimulus interval of 1000 ms and 500 ms, respectively. A fixation cross point was presented for 500 ms prior to the presentation of a new sentence material. Each segment subtended a visual angle of 4° and was presented in black lettering against a gray background. After the presentation of a sentence, participants were required to judge whether the preceding sentence was semantically congruent or not, and press a keyboard button (F or J, respectively) to give a response as fast as possible. The response hand was counterbalanced across participants. The participants were allowed a brief break of approximately 10 min between sessions. 4.3. Electroencephalogram (EEG) recording

4. Experiment 2: Event related potential (ERP) experiment

We used a BrainAmp standard amplifier (Brain Products, Germany) with 32 Ag/AgCl electrodes in an actiCAP (Brain Products, Germany) for the EEG recording. The electrodes were sited in accordance with the international 10–20 system. Eye movements were separately recorded using two pairs of electrodes that were placed vertically and horizontally with respect to each eye. In offline pre-processing, the electrooculogram was corrected using the independent component analysis method (Makeig, Bell, Jung, & Sejnowski, 1996). The impedance of all the electrode sites was checked prior to data acquisition and maintained below 5 kΩ during the recording. The EEG and EOG recordings were amplified and digitized online with 250 Hz sampling rate. Online recordings were referenced to the electrode attached on the tip of the nose.

4.1. Participants and materials A total of 17 right-handed native speakers of Korean (8 women, with a mean age of 22 years, which ranged from 20 to 26 years), with normal or corrected-to-normal vision, participated in EEG experiment. They were undergraduate students at Konkuk University in Seoul, S. Korea. The EEG was recorded in accordance with the ethics guidelines established by the Declaration of Helsinki (World Medical Association, 1964; 2002). All participants took part in the experiment voluntarily and provided written consent prior to the start of the experiment. After the experiment, they received $30 for participation. All materials used in the ERP experiment were identical to the ones in the self-paced reading (SPR) experiment (see section 3.2)

4.4. Data analysis

4.2. Procedure

For the behavioral analysis, we calculated the percentage of ‘Yes’ response, which indicated that the preceding sentence was judged as semantically congruent in the sentence acceptability task performed at the end of sentences. The data were then analyzed using a repeated measures ANOVA, with a 2 (adjacent congruence vs. incongruence) × 2 (distant congruence vs. incongruence) factorial design.

Participants requested to minimize the body movement during EEG acquisition. All materials were presented using a specialized presentation software package (E-Prime 2.0 Professional, Psychology Software Tools, USA). Sentences were presented in the rapid serial visual 32

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Table 3 The summary of statistical analysis for the ‘Yes’ reading time. N1

Vr

N2 **

Adv.

Vm *

F1(1,53) = 8.804* F2(1,42) = 3.874*

Adjacent congruence

F1(1,61) = 2.541 F2(1,43) = 0.219

F1(1,60) = 53.694 F2(1,43) = 77.405**

F1(1,58) = 1.805 F2(1,42) = 1.469

F1(1,58) = 4.094 F2(1,42) = 1.238

Distant congruence

F1(1,61) = 0.816 F2(1,43) = 0.273

F1(1,60) = 1.805 F2(1,43) = 3.685^

F1(1,58) = 0.925 F2(1,42) = 0.088

F1(1,58) = 0.049 F2(1,42) = 0.097

F1(1,53) = 5.431* F2(1,42) = 3.185^

Adjacent × Distant

F1(1,61) = 0.233 F2(1,43) = 0.020

F1(1,60) = 1.185 F2(1,43) = 0.863

F1(1,58) = 0.633 F2(1,42) = 0.236

F1(1,58) = 1.424 F2(1,42) = 0.595

F1(1,53) = 4.005* F2(1,42) = 0.631

p < 0.01 **, p < 0.05 *, 0.05 < p^ < 0.1.

The EEG data were re-referenced to the average of the left and right mastoids and filtered using a 0.1–30 Hz band-pass filter offline.2 Artifacts surpassing an amplitude of ± 70 μV, or above an amplitude of 50 μV within a moving 4-ms interval, were excluded from further processing. After the pre-processing, the data were epoched from −100 ms to 900 ms to the onset of the target words and corrected by a 100-ms pre-stimulus baseline. Since it was challenging to specify a pre-defined time windows for analyzing EEG data (Bornkessel-Schlesewsky et al., 2011), the time windows for the statistical analysis were selected based on the visual inspection of data. Whole time windows were selected on the basis of the grand-averaged waveforms and their individual variations. Repeated measures ANOVA was used to compare the mean amplitude of AI (average of AIDC and AIDI) to AC (average of ACDC and ACDI), at the N1 and Vr position, for midline and lateral sites separately. For the analysis of the midline area, the Fz, Cz, Pz, and Oz electrodes were used as a single ROI, whereas the average value of four or five adjacent electrodes were used as the ROI for the lateral analysis including laterality (left or the right) and anteriority (anterior or posterior) as follows: left-anterior (LA; FC1, FC5, F3, and C3), right-anterior (RA; FC2, FC6, F4, and C4), left-posterior (LP; CP1, CP5, P3, P7, and O1), and right-posterior (RP; CP2, CP6, P4, P8, and O2). For the other critical words (N2 and Vm), the repeated measures ANOVA with the distant congruence (congruence vs. incongruence), the adjacent congruence (congruence vs. incongruence) and ROI factor was performed. An additional omnibus ANOVA was performed at the N2 and Vm positions to confirm the distant congruence effect, without regarding the adjacent congruence factor.

This result indicated that when semantically congruent nouns appeared at an adjacent noun region right after the adjectives, the participants did not consider the possibility of distant congruence anymore. However, when incongruent nouns were used as adjacent nouns, e.g., in the AIDC and AIDI conditions, participants took the semantic congruence between preceding adjectives and distant nouns into account, in order to establish a reasonable semantic representation. 4.5.2. Event related potential (ERP) results 4.5.2.1. Visual inspection of the critical regions: from N1 to Vm. Before the statistical analysis, we examined the brainwave in the entire critical region (from N1 to Vm) visually. This procedure was carried out not only to confirm the time-window of the critical words for the statistical analysis but also to take the potential spillover effects into account in case there are any ERP waveform differences prior to the onset of the word of interest.5 As shown in Fig. 3, on the ± 5 μV scale, the difference between conditions was visually observed in the 350–600 ms time window after the onset of the relativized verb and main verb, respectively. Since the differences in other critical regions were slightly unclear, we increased the amplitude scaling and found differences after the onset of N2. The results of ERP analysis for each critical word have been reported in later sections. 4.5.2.2. At the N1 position. Since the lexical items used in the ACDC and ACDI condition, and the AIDC and AIDI condition were identical at the N1 and Vr position, respectively, we averaged the amplitude of ACDC and ACDI, which was used as the value of adjacent congruence in the analysis at the N1 and Vr position. The average amplitude of AIDC and AIDI was used as the value of adjacent incongruence as well. As shown in Fig. 4, there was no difference between AC (i.e., the average of ACDC and ACDI) and AI (i.e., the average of AIDC and AIDI), both in the midline (F(1,16) = 0.022, n.s.) and in the lateral analysis (F (1,16) = 0.20, n.s.).

4.5. Results 4.5.1. Sentence acceptability task Participants performed a sentence-acceptability task, in which they judged whether the experimental sentences were semantically acceptable or not, immediately after the whole sentence was presented on the screen. The percentage of ‘Yes’ response was calculated across the conditions. The acceptability for the four conditions was as follows: 89% for ACDC, 87% for ACDI, 44% for AIDC, and 29% for AIDI. A repeatedmeasures ANOVA including two within-subjects factors labeled as “adjacent congruence” and “distance congruence” revealed a significant main effect of the adjacent congruence (F(1,16) = 175.83, p < 0.001; AC = 88% vs. AI = 36%)3 and the distant congruence (F (1,16) = 16.275, p < 0.01; DC = 66% vs. DI = 58%).4 In addition, the interaction effect between these factors was also significant (F (1,16) = 8.466, p < 0.01). Post-hoc analysis revealed that the distant congruence effect was only significant when the adjective and adjacent noun was semantically incongruent (F(1,16) = 13.208, p < 0.01; AIDC = 44% vs. AIDI = 29%).

4.5.2.3. At the Vr position. We observed significant differences in the 350–600 ms time window across all conditions at the Vr region (Fig. 5). Repeated measures ANOVA with adjacent congruence and topographical factors (ROI) revealed a significant main effect of adjacent congruence in the midline (F(1,16) = 7.963, p < 0.05) and lateral (F (1,16) = 7.163, p < 0.05) regions. A significant interaction effect was observed between adjacent congruence and ROI in the midline analysis (F(3,48) = 4.642, p < 0.05), and a marginally significant one in the lateral analysis (F(3,48) = 2.420, 0.05 < p < 0.1). Additional analyses confirmed that a negativity effect was elicited in AI conditions in all areas, but the effect was larger in the midline-posterior region around Cz and Pz than in the anterior region. 4.5.2.4. At the N2 position. At the N2, critical differences due to long-

2 This high-pass filter value was recently confirmed as the one that does not introduce any artefactual effects (Tanner, Morgan-Short, & Luck, 2015). 3 AC = average of ACDC and ACDI; AI = average of AIDC and AIDI. 4 DC = average of ACDC and AIDC; DI = average of ACDI and AIDI.

5 We did not find evidence for any ERP waveform differences prior to the onset of the word of interest in the relative clause region (i.e., N1, Vr, and N2). This implies that there were no spillover effects in this critical region.

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Fig. 3. (a) The grand-average ERP waveforms from −100 ms to +6000 ms of N1 onset at the 9 main electrodes. (b) Enlarged image focusing on the findings at the Cz channel. The ERP differences observed by the visual inspection were clear in the solid line boxes and vague in the dotted line boxes.

distance congruence factor were observed in the 300–600 ms time windows (Fig. 6). In the midline analysis, repeated-measures ANOVA with adjacent congruence (2) × distant congruence (2) × ROI (4) revealed a significant main effect of distant congruence (F(1,16) = 6.324, p < 0.05) and ROI (F(3,48) = 6.169, p < 0.05). The analysis of the lateral regions revealed a main effect of the distant congruence (F(1,16) = 6.351, p < 0.05), an interaction effect between the distant congruence and the laterality (F(1,16) = 4.399, p = 0.05). Since the difference between AIDC and AIDI conditions is more critical at the N2 position, we abstracted the two conditions and performed additional repeated-measures ANOVA with distant congruence (2) × ROIs (4) in the midline and with distant congruence (2) × anteriority (2) × laterality (2) in the lateral region. As a result, a significant main effect of the distant congruence (AIDC −0.614 μV vs. AIDI −1.497; F(1,16) = 5.720, p < 0.05) and ROIs (F(1,16) = 4.907, p < 0.01) was revealed in the midline. In the lateral analysis, a significant main effect of the distant congruence (AIDC −0.335 μV vs. AIDI -1.079; F(1,16) = 4.953, p < 0.05) was observed and a three-way interaction effect (F(1,16) = 3.553, 0.05 < p < 0.1) was marginally significant. Descriptive statistical analysis showed that the distant congruence effect was larger in the anterior (AIDC −0.598 μV vs. AIDI −1.591 μV) than in the posterior region (AIDC −0.071 μV vs. AIDI −0.568 μV), and larger in the right (AIDC −0.359 μVvs. AIDI −1.181 μV) than in the left region (AIDC −0.310 μV vs. AIDI −0.977 μV) of the brain.

The results at the N2 position showed that when the semantically congruent noun appeared as N2, participants recalculated the semantic dependency immediately and tried to integrate distant noun with the preceding adjectives, resulting reduced N400 at N2 in AIDC compared to AIDI condition. 4.5.2.5. At the Vm position. As shown in Fig. 7, there were significant differences in the 350–600 ms time window between the conditions at the Vm region. Repeated measures ANOVA with adjacent congruence (2) × distant congruence (2), and ROI (4) demonstrated the significant main effect of adjacent congruence on the midline (F(1,16) = 15.182, p < 0.01) and lateral (F(1,16) = 19.004, p < 0.001) regions. Moreover, there was a significant interaction between adjacent congruence and distant congruence on the midline (F(3,48) = 5.589, p < 0.05) and on the lateral region (F(3,48) = 4.356, p = 0.05). Further analysis using compared ttest showed that when the distant noun was incongruent with the adjective, a congruence between an adjective and an adjacent noun had a critical role in the sentence-final verb processing, and the effect was significant both on the midline (ACDI 0.512 μV vs. AIDI −1.016 μV; t (1,17) = 4.909, p < 0.001) and lateral region (ACDI 0.680 μV vs. AIDI −0.733 μV; t(1,17) = 4.909, p < 0.001). However, when the distant noun was congruent with the preceding adjective, the adjacent congruence effect at the main verb was only marginally significant in the lateral region (ACDC 0.614 μV vs. AIDC −1.100 μV; t(1,17) = 2.489, 0.05 < p < 0.1).

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Fig. 4. The results at the N1: (a) The grand-average ERP waveforms from AC and AI conditions at each electrode site. (b) Topographies for AC and AI conditions in 300–500 ms time window and mean amplitude on the midline and lateral regions in the same time window.

The most critical question at Vm was whether the distant congruence factor would be maintained until the Vm or not. Therefore, we compared the AIDC and the AIDI condition as well. There was a significant difference between AIDC and AIDI condition on the midline (AIDC −0.200 μV vs. AIDI −1.106; F(1,16) = 5.751, p < 0.05) and on the lateral region (DC −0.110 μV vs. DI −0.733; F(1,16) = 4.438, p = 0.05). Since the larger negative deflection of brainwave was elicited in the AIDI condition compared to the AIDC condition around Cz and Pz regions, we concluded that distant congruence, as well as an adjacent congruence, influenced the on-line processing up to the sentence-final position.

because semantic strangeness between two successive words is prevalent in the head-final languages like Korean.6 Therefore, the processor might well hold the completion of an NP, whose whole meaning would be very difficult to be derived based on the principle of compositionality. Otherwise, an increased reading time and N400 component, which is a typical index of processing load caused by semantic violation (see Kutas & Federmeier, 2011; Kutas, Van Petten, & Kluender, 2006, for review), should have been observed for the N1 region.7 Assuming that the processor did not construct the [NP A N]

6 As an anonymous reviewer pointed out, 18% ‘No’ responses to the AIDC and AIDI conditions at the N1 position during the SPR experiment appears to be incompatible with this analysis. Actually, the discrepancy between the stop making sense data and the RT/ERP data is not restricted to the N1 alone. Notice in this regard that the ‘No’ responses to the AI conditions at the Vr position (30–35%) did not reach the expected level, although the ERP response to the Vr clearly indicated the unconscious processing load (N400). Overall, the stop making sense data based on the off-line processing should rather be taken to show a general tendency of processing load, not demonstrating the exact picture of the underlying processing mechanism. 7 According to Nam and Hong (2016), e.g., the classical N400 was elicited by the N in the semantically incongruent A-N string during reading comprehension of Korean simple declarative sentences. The direct comparison between the null-effect observed in the current experiment with the N400 enhancement reported in Nam and Hong (2016) is of course hardly possible due to the difference in experiment materials.

5. Discussion The most interesting finding of our experiments was that the semantic incongruence between adjectives and the adjacent nouns did not cause any kind of processing load at the N1, neither in terms of reading time data, nor in terms of ERP responses: There was no significant increase in reading time in the AI conditions (AIDC and AIDI), compared to the AC conditions (ACDC and ACDI); there was also no difference in ERP responses to N1 in all conditions. We interpret the observed ‘null-effect’ of A-N semantic incongruence as indicating that although the processor should have at least evaluated whether the A and the N1 are semantically compatible, the detected semantic strangeness caused no processing load in terms of measurable indices of unconscious cognitive processes, probably 35

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Fig. 5. The results at the Vr: (a) The grand-average ERP waveforms of AC and AI conditions at each electrode site. (b) Topographies for AC and AI conditions in the 350–600 ms time window and mean amplitudes on the midline and lateral regions in the same time window.

immediately, there appeared to be a couple of alternative analyses of the null-effect of A-N1 semantic incongruence, and the corresponding interpretations of the reading time and ERP patterns observed during the follow-up processing stage of the experiment materials.

reflected the processor’s attempt to represent the whole structure of a relative clause as a wrap-up (Van Petten & Kutas, 1991; Osterhout & Holcomb, 1992, 1993). Nonetheless, some additional considerations are required. Although a Vr apparently signaled a boundary of an ERC, it should be pointed out that an argument to be integrated to the verb argument structure is still missing at that region, i.e., the rightward-moved head noun. Therefore, it is somewhat challenging to regard the N400 effect in response to the Vr as identical to the usual wrap-up at the ‘real’ sentence-final position. Furthermore, it is unlikely that the wrap-up-related N400 should only be observed in specific experimental conditions. The fact that the N400 at the Vr has been elicited only in the AI conditions, but not in the AC conditions, suggests that the observed N400 enhancement might be related to the preceding adjective and N1 semantic mismatch, which contradicts with the ERC analysis (see the following discussion). Therefore, the ERC analysis does not adequately explain the processing load observed in the Vr region. This approach would be more tenable if the (in)congruence effect between a still dangling adjective and the incoming head noun could be confirmed. An ERC construction ‘A [RC N1…]’ at the N1 region was chosen to rescue the adjective from a meaning conflict to the current N1, expecting for another noun with a more compatible meaning (i.e., most probably the head noun N2). Without evidence to show that such a long-distance A-N2 integration was in fact attempted, the ERC analysis would become much less plausible. In this regard, the observed anterior sustained negativity in 350–600 time window at the N2

5.1. An ERC (embedded relative clause) analysis Where the processor did not build the simplest [NP A N] at the N1 region, the first alternative choice for the processor is to begin with an embedded relative clause (ERC, henceforth), such as ‘… A [RC N …]’ (see section 2), whereby the A-N1 integration is automatically impossible due to the intervening clause boundary. In such a construction, the null-effect of A-N1 semantic conflict at the N1 region was an expected result. However, the succeeding reading time and ERP responses to incoming words should also be accounted for in a consistent way to validate this analysis. If the construction of an ERC had already begun, the incoming Vr would meet the processor’s expectation for the completion of unfolding relative clause. This implied that no extra loads were expected for processing Vr. However, in comparison to AC conditions, both a longer reading time and N400 effect were observed at the Vr region of AI conditions. Such processing loads cannot be interpreted to reflect the preceding AN1 semantic incongruence since the processor expected the occurrence of a Vr and there was still no reason to combine A and N1, which were separated by a clause boundary. Therefore, the N400 effect likely 36

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(a)

Adjacent congruence and distant congruence (ACDC)

Adjacent incongruence and distant incongruence (AIDC)

Adjacent congruence and distant congruence (ACDI)

Adjacent incongruence and distant incongruence (AIDI)

(b)

Adjacent incongruence and distant congruence (AIDC)

Adjacent incongruence and distant incongruence (AIDI)

Fig. 6. The results at the N2: (a) The grand-average ERP of all 4 conditions at each electrode site. (b) The grand-average ERP waveforms of AIDC and AIDI conditions at each electrode site. (c) Topographies of AIDC and AIDI conditions in the 350–600 ms time windows and mean amplitudes on the midline and lateral regions in the same time window.

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Fig. 6. (continued)

position of AIDI condition appears to be somewhat different from the ERP response expected under the ERC analysis. The reason is that if the processor was waiting for an additional N which is semantically congruent with the dangling A, the A-N2 incongruence should have caused the classic N400 effect. On the contrary, the fact that an anterior sustained negativity was elicited by the N2 of AIDI condition implies that something more is going on at the N2 position, which is difficult to clarify under the ERC analysis (See below). Overall, the reading time and ERP response data from the experiments of the current study appeared to be largely incompatible with the results of the ERC analysis, which assumes a type of predictive sentence processing in the sense that the A-N1 semantic mismatch immediately predicts an embedded relative clause. Importantly, this result contrasts with the findings from previous ERP studies on the adjacent or long-distance classifier-noun dependencies in Mandarin Chinese. The Chinese language takes advantage of many kinds of noun classifiers that occur only with a specific subset of lexically/semantically associated nouns, and the relative clause in Mandarin Chinese (like in Korean) is head-final, although in other aspects, Chinese is an SVO language. Therefore, given an intervening object relative clause, a classifier might not modify an adjacent noun, but instead, a long-distant head noun of that relative clause, similar to the use of adjectives in Korean:

However, there is still room for these seemingly incompatible findings to be compromised due to a difference in experimental materials. As Hsu et al. (2014) pointed out, the ‘demonstrative-CL’ combination used in Chen et al. (2013)’s experiment might well have referred to more specific and definite nouns and have been a more useful cue to help the processor in making explicit RC predictions than the ‘numeralCL’ combinations used in Hsu et al.’s experiment. In other words, the possibility or strength of the RC prediction by CL-noun mismatch in Chinese appears to increase proportionally to the specificity of the semantic restriction provided by the preceding ‘determiner-CL’ string. Given this, the Korean bare adjectives in our experiment, which lacked CL-like specific semantic cooccurrence restrictions for the upcoming noun, were likely almost useless for the RC prediction, in accordance with our rejection of the ERC analysis. Another difference between the impacts of Chinese CL-noun and Korean adjective-noun (mis)match on the processing of unfolding sentence structure is highlighted by the apparent contrast between ERP responses observed at the N2 position. That is, Hsu et al. (2014) reported the enhancement of N400 as a result of CL-N2 mismatch, and the enhancement of P600 reflecting the processing of long-distance CL-N2 dependencies (irrespective of the CL-N2 (mis)match, and only under the CL-N1 mismatch), which is, in our view, consistent with the findings of the RC prediction analysis. At any rate, the anterior sustained negativity commonly elicited by the N2 in the AI conditions of our experiment strongly suggests that the processing of Korean long-distance A-N dependencies separated by an intervening relative clause occurs differently. In conclusion, the ERC analysis in our study is not tenable, not only in terms of the characterization of the observed ERP components but also with respect to comparisons with previous findings from Chinese studies adopting similar experimental paradigms. Hence, we must consider an alternative scenario for the processing of the sentence constituents up to the N2 position, temporarily delaying the characterization of the ERPs elicited by the final Vm of the sentence (See below).

Manipulating the semantic relationship between the classifier (CL, henceforth) and N1/N2 in structures like that in (5), many previous studies investigated how temporary CL-N1 semantic incongruence and long-distance classifier-noun dependency are processed in Mandarin Chinese, focusing mainly on whether the CL-N1 mismatch contributes to the generation of a relative cluase (RC) prediction (Hsu, Phillips, & Yoshida, 2005; Hsu, Hurewitz, & Phillips, 2006; Wu, Haskel, & Andersen, 2006; Wu, Kaiser, & Andersen, 2009). Specifically, ERP evidence on whether the temporary CL-N1 mismatch is effective in relative clause prediction appears to not be coincident but suggestive in some aspects. On the one hand, Chen, Xu, Tan, Zhang, and Zhong (2013) provided ERP evidence indicating that the CL-N1 mismatch leads the processor to prepare for an upcoming relative clause, hence reducing the P600 component, which is generally taken to be an index of the processing cost required for a structural reanalysis (Friederici, 2002; Kaan & Swaab, 2003; Osterhout & Holcomb, 1992): The occurrence of ‘DE’ forces the processor to reanalyze a declarative sentence as a relative clause. On the other hand, Hsu et al. (2014) showed that given the CL-N1 mismatch, a midline negativity and not a P600 reduction was observed at the DE position, following an anterior midline negativity at the N1 position. Together, these results implied that RC occurrence was not predicted by the processor (Hsu et al., 2014).

5.2. A late structure building (LSB) analysis Since the ERC analysis did not provide a consistent picture of the disambiguation process, another approach based on the peculiarities of head-final languages was taken into consideration. In line with the head-driven parsing model (Pritchett, 1991, 1992), in head-final languages, it was conceivable that the integration of incoming words into more complex sentence constituents was delayed temporarily until clause/sentence-final verb had occurred. We assumed that this tendency may be extended to the local level of phrase structure building, e.g., to the construction of single sentence constituents like NP, if the involved direct integration led to a certain amount of (potentially unnecessary) processing load. In other words, it was possible that the processor did not build any kind of complete or partial constituent structure at all at the N1 region due to the semantic strangeness at hand, but waited until a much clearer clue was available. In brief, the absence of N400 at the N1 could be attributed to a kind of ‘late 38

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structure building (LSB)’ strategy in head-final languages, by which the processor delays the construction of a phrase (NP in the current case) temporarily in order to avoid a meaning conflict. However, even if the processor had not built an NP or a partial relative clause from semantically incongruent A and N, such a ‘tolerance’ would not be maintained after a relativized verb appeared, which

explicitly requires that the preceding words be organized into a relative clause. This means that the A-N1 incongruence effect, whether it be an increased reading time or corresponding ERP response, should also become observable no later than at the Vr position. This scenario was also compatible with a recent suggestion of ‘wait and see’ strategy, according to which the processor of head-final languages might

(a)

Adjacent congruence and distant congruence (ACDC)

Adjacent incongruence and distant incongruence (AIDC)

Adjacent congruence and distant congruence (ACDI)

Adjacent incongruence and distant incongruence (AIDI)

Adjacent incongruence and distant congruence (AIDC)

Adjacent incongruence and distant incongruence (AIDI)

(b)

Fig. 7. The results at the Vm: (a) The grand-average ERP waveforms of all 4 conditions at each electrode site (b) The grand-averageERP grand-average waveforms from of AIDC and AIDI conditions at each electrode site (c) Topographies of AIDC and AIDI conditions in the 500–700 ms time windows and mean amplitudes on the midline and lateral regions in the same time window.

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Fig. 7. (continued)

two Ns are compared at the conceptual level. Interestingly, this implies that the processing of strict head-final languages like Korean may depend on a type of hybrid mechanism by which semantics-driven and syntax-driven processing are applied interchangeably. More evidence appears to be required for the clarification of this important issue, and a deeper understanding of anterior sustained negativity will also contribute greatly to this. Crucially, the aforementioned analysis implied also that after a breakdown of A-N1 integration at the clause-final verb (=relativized verb), the integration of the same adjective with another incoming noun becomes obligatory, with no delay until the main verb comes in, i.e., before the sentence-final verb position. Therefore, an attenuated or moderately revised version of the head-driven parsing model is required, where the ‘verb as a borderline strategy’ might be omitted in order to avoid the repetition of the processing breakdown of the same kind. Finally, one remaining issue is whether the LSB analysis also provides a reasonable account of the ERPs elicited by the sentence-final main verb Vm. In the AI conditions where the processor had to evaluate the long-distance A-N2 dependency, the extra cost due to the additional processing was reflected as ERP responses to the Vm in a distinctive and explainable manner. That is, the N400 was elicited by the Vm in the AI conditions when compared to that of AC conditions, which demonstrated that the long-distance A-N2 integration did in fact occur, and also that the negative effect of the local semantic mismatch spilled over further and raised the cost for the representation of the meaning of the whole sentence, irrespective of whether the long-distance integration at the N2 position succeeded. Moreover, the fact that the N400 amplitude observed in the AIDI condition was larger than that in the AIDC condition reflects the processor’s detection of the ultimate ungrammaticality of AIDI sentences, signaled by the occurrence of the main verb. In contrast, there was practically no ERP difference between ACDC and ACDI conditions, implying that the processor does not calculate the long-distance dependency any more given a successful A-N integration at the local level, even under specific syntactic circumstances in which the occurrence of an additional noun is expected. Taken together, the LSB analysis, which was corroborated with the head-driven parsing model, appeared to provide a more plausible description of the time course of the disambiguation process that was investigated in the current study.

temporarily delay the integration of incoming words waiting for a definitive clue indicating in what manner they should be integrated (Kwon, Polinsky, & Kluender, 2006; Kwon, 2008). Thus, the N400 component elicited by the Vr of adjacent incongruent conditions could be interpreted as reflecting the semantic incongruence effect of the preceding NP. Consequently, the processor would immediately try to find a way out from such a semantic conflict, probably provided by another upcoming N which is semantically compatible with A. When the processor in fact encountered the head noun N2, it had to determine whether this N2 is a better candidate for the semantic integration with the preceding A, by comparing the semantic features of N2 with those of N1 on the one hand, and their compatibility with the meaning of A on the other. We believe that this kind of processing efforts might have well been the reason for the enhancement of an anterior sustained negativity at the N2 position. Notice that in the N2 position of the AIDI condition where the anterior sustained negativity was observed, the processor detected that the additional N2 is semantically incongruent with the A as well. In such a circumstance, it is conceivable that the processor is forced to compare semantic compatibility of both N2 and N1 with the preceding A respectively in order to find a way out from the ultimate processing breakdown. In other words, the processor tried vainly to combine the A with one of two nouns which were equally incongruent with it. Interestingly, the fact that such a processing effort caused the enhancement of an anterior sustained negativity appears also to have something with the findings of previous ERP studies on the ambiguity resolution. That is, in a series of ERP studies, the enhancement of an anterior sustained negativity was attributed to the resolution of an ambiguous pronoun (Nieuwland & van Berkum, 2006; Nieuwland, Otten, & Van Berkum, 2007; Van Berkum, 1999, 2003, 2004). Nieuwland and van Berkum (2006), for instance, showed that ambiguous pronouns elicited a sustained, frontal negativity shift relative to non-ambiguous pronouns. Although the processing task involved in the determination of discourse reference of pronouns is different from integrating an adjective with one of competing nouns, the underlying mechanism might be similar in the sense that a unique dependency relation should be established between multiple candidates. Moreover, the absence of positive ERPs (e.g., P600) at the N2 position in the AIDI condition suggests that the calculation of meaning compatibility between A and N1/N2 did not occur using the structural reanalysis, nor in terms of structural dependency. We speculate that this is because if the processor maintains a specific syntactic structure, the rapid evaluation of meaning relationships, which is needed to avoid a processing breakdown, might be disturbed. Notice that maintaining the current relative clause construction that includes the A would not provide a possible method for combining the A with the N2 that is outside that relative clause. In contrast, in the reanalyzed construction in which the A is outside the relative clause, the structural possibility to combine the A with the N1 within the relative clause disappears. In this regard, the processor appears to have adopted a purely lexical strategy for the resolution of A-N1/N2 dependency, through which the isolated A and the

6. Conclusion Overall, the current study demonstrated that the local A-N integration in Korean might be completely renounced at least temporarily, given the A-N semantic incompatibility. This implied that the option of not completing a phrase at the local level, even during on-line sentence comprehension, is available in Korean. However, the organization of all the provided words into a partial phrase structure at critical points is inevitable, even though that critical point need not be the clause/sentence-final verb as is generally assumed in the head-driven parsing model. In other words, local integration 40

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driven by syntax could be somewhat loosened based on the verb-final property, and also by the semantically-driven processing strategies in head-final free word order languages, such as Korean. In conclusion, we argue that the need for repeated disambiguation at almost every point of on-line sentence comprehension in head-final languages forces the processor to adopt a hybrid solution, which might temporarily victimize the convenience of the strict incremental processing, but nonetheless minimizes the total cost for successful phrase structure building.

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