Glossa Psycholinguistics

2.1 Perspective-sensitivity of ziji

Below, we review the core concepts of perspective-sensitivity, topic prominence and verb bias, and discuss how they are likely to impact reflexive resolution in Chinese given prior linguistic and psycholinguistic work. We first introduce the perspective-sensitivity property of ziji as this provides an important foundation for considering topic prominence.

As mentioned above, ziji is often seen as a logophoric reflexive due to its perspective-sensitivity. Logophoric pronouns are typically coreferential with the sentence-internal subject whose speech or mental state is reported (e.g. Clements, 1975; Hagège, 1974) – the person whose speech/thoughts/perspective is being conveyed. Sells (1987) applied the notion of logophoricity to languages that allow LD reflexivization and outlined three primitive roles for antecedents of logophoric reflexives:

The antecedent of ziji has been argued to exhibit all three properties (e.g. Huang & Liu, 2001), as LD binding of ziji can be licensed by antecedents in Source, Self, and Pivot roles. In the following sentences adapted from Huang and Liu (2001, p. 314), John is an intentional speaker or Source in (4a). Example (4b) involves backward binding, where the antecedent John does not structurally dominate (i.e. c-command) ziji. But binding is licensed because the psychological predicate ‘very happy’ makes John the Self. Ex.(4c) describes the situation that John is in with respect to a specific time and location, which makes John the Pivot.

In the linguistic literature, various terms have been used to refer to the phenomena of logophoricity and perspective-sensitivity in (4a–c). For example, Sells (1987, fn.15) and Huang and Liu (2001) argue that Pivot, Source, and Self involve “empathy” with the antecedent. In this context, “empathy” refers to the “speaker’s identification with a person/thing that participates in an event or state” (Kuno, 1987, p. 206). It typically involves taking on an event participant’s perspective or point-of-view (Huang & Liu, 2001; Iida, 1992; Kuroda, 1965; Kuno & Kaburaki, 1977; Oshima, 2007; Sells, 1987). In this paper, when we use the term “empathy” in discussing prior work on some occasions, it can be construed as synonymous with “perspective-taking.” Thus, in (4a–c), if John is construed as the antecedent of ziji, he is the perspective center: the reader assumes John’s perspective and views the event from his point of view. In fact, some researchers argue that LD binding of ziji necessarily involves perspective-taking (Huang & Liu, 2001; Huang et al., 2009; Pan, 1997; Wang & Pan, 2015; but also see Charnavel et al. (2017) for a review of alternative approaches).

Note that the perspective-sensitivity property attributed to ziji differs sharply from the morphologically complex form ta-ziji. It is generally agreed that, unlike ziji, ta-ziji is not perspective-sensitive. LD binding is highly restricted for ta-ziji and seems to be allowed only when the local NP is inanimate (e.g. Pan, 1998; Pan & Hu, 2002). Whenever the local antecedent is animate, LD binding is deemed impossible as in ‘Zhangsan_i knows Lisi_j likes ta-ziji_*i/j’ (Pan, 1998, p. 781). This coreference pattern contrasts sharply with the logophoric use of ziji shown above. To illustrate the difference, we replaced ziji in (4a–c) with ta-ziji. As can be seen in (5a–c), LD binding by Source, Self, or Pivot is highly degraded according to native-speaker judgment.

2.2 Topic prominence and ziji/ta-ziji

As shown above, LD ziji is sensitive to perspective-taking. We now consider how topic prominence can play a role in the processing of ziji. According to the Topic Empathy Hierarchy (Kuno, 1987), given an event involving two participants A and B such that A is a discourse topic, it is easier to take the perspective of A than B. Although Kuno’s work is not based on Chinese ziji, it makes clear predictions. Suppose we have two participants in a discourse as in (6), ‘chairman’ and ‘Director Li’. The first sentence introduces ‘chairman’ in subject position and describes an event about him. He can be easily construed as the discourse topic. Thus, the Topic Empathy Hierarchy predicts that readers should prefer the perspective of ‘chairman’, and thus the perspective-sensitive ziji should tend to be interpreted as referring to the perspective center ‘chairman’ (rather than ‘Director Li’). In the rest of this paper, we refer to this phenomenon as the topic prominence/topicality effect. Building on Kuno’s work on the link between topics and empathy/perspective, we assume that any potential topic prominence effects displayed by ziji are related to its perspective-sensitivity.

What about non-perspective-sensitive ta-ziji? The claims of the Topic Empathy Hierarchy are not relevant for ta-ziji since it shows no signs of perspective-sensitivity in (5a–c). But recall that Pan and Hu (2002) noticed that, in certain contexts, ta-ziji can be LD-bound. Most relevant for us, they argue that this is due to ta-ziji being sensitive to a prominence constraint. In their terminology, “prominence” refers specifically to the grammatical role and the animacy of the antecedent. However, in light of a large amount of work showing that grammatical role and animacy are only two of the many factors that influence the prominence of referents, it seems reasonable to hypothesize that ta-ziji may be sensitive to topic prominence as well. Thus, in this work, we ask the following question: do Chinese speakers consider LD binding of ta-ziji when the non-local antecedent is prominent at the discourse level?

2.3 Verb bias

We have so far sidestepped an important factor: verb semantics. Example (6) uses the verb tiji (‘mention’) in the second sentence. But if the verb is changed to a self-directed verb like xuanyao (‘brag’), the sentence becomes more ambiguous. Now, it is more plausible that Director Li brags about his own skills as opposed to the chairman’s skills. Thus, when ziji or ta-ziji occurs with a self-directed verb like xuanyao (‘brag’), the verb’s lexical semantics, locality, and topic prominence push in different directions (towards the local antecedent ‘Director Li’ or the discourse topic ‘chairman’). Faced with this dilemma, how do Chinese speakers interpret ziji or ta-ziji? In other words, how are different kinds of information (syntactic, semantic, and pragmatic) prioritized?

We explore the role of verb semantics by testing the effects of verb directedness. Self-directed verbs (or “introverted” verbs) describe actions that “one generally performs upon one’s self” and other-directed verbs (or “extroverted verbs”) denote actions that one “usually performs towards others” (Haiman, 1983, p. 803; also see e.g. Gast, 2006; König & Siemund, 2000). There are also neutral verbs which are ambiguous regarding whom the action is directed at. Verb bias has been frequently used in previous studies on ziji to push comprehenders to construct local or non-local dependencies (He, 2014; Li & Zhou, 2010; Schumacher et al., 2011). However, these studies do not speak directly to the question of whether verb effects interact with a potential topic prominence constraint and the locality constraint in the processing of ziji/ta-ziji.

Prior work by Lu (2011) on Taiwan Mandarin Chinese suggests that a conflict between verb semantics and the locality constraint as in (7) does not always lead to processing difficulty. Lu tested sentences with triple-clause structures where ziji or ta-ziji occupies the position of the subject of the most embedded third clause. As shown in (7), the semantics of the verb after (ta-)ziji biases either towards the “local” antecedent (‘receive’ biasing ‘public’) or towards the non-local antecedent (‘deliver’ biasing ‘mailman’). It is worth mentioning that the verb bias manipulated by Lu (2011) is more about real-world plausibility than verb-directedness.

Given what we know from earlier research, we can have the following expectations for (7). As the locality constraint pushes (ta-)ziji to look for a structurally closer antecedent but a LD-compatible verb such as ‘deliver’ pushes for the matrix subject ‘mailman’, one would expect a clash of the structural constraint and semantic bias at the disambiguating verb. Interestingly, Lu (2011) found that these kinds of clashing configurations elicited reading slowdowns with ta-ziji but not with ziji. Lu’s account of this asymmetry largely boils down to different degrees of sensitivity to the locality constraint (ziji is less sensitive to locality than ta-ziji, under this view). Lu’s other finding is that participants preferred local antecedents for ta-ziji even with ‘receive’, suggesting locality is more important for ta-ziji than verb bias, which we will assess further in this study.

4.1 Materials and design for Experiments 1a and 1b

Experiments 1a and 1b used the same materials and design. The factors context (neutral/biased) and verb bias (self-directed/other-directed) were crossed in a 2x2 factorial design. The label neutral context refers to a context that lacks a clear discourse topic (see (8a,b)). In neutral contexts, no individual character is mentioned in the first sentence, and thus no referent is established in prior discourse as topical. We contrast this with biased contexts where the first sentence establishes the non-local antecedent (e.g. ‘chairman’) as the discourse topic (see (8c,d)) by introducing it in subject position and providing information about it. We refer to this context manipulation as a discourse topic manipulation. Note that in biased contexts, the matrix subject of the critical sentence starts with the pronoun ta to avoid incurring a repeated name penalty (e.g. Almor, 1999; Gordon et al., 1993; Garrod et al., 1994).

The critical sentence contains either a self-directed verb (e.g. ‘brag’) that biases the local reading of ziji or an other-directed verb (e.g. ‘flatter/praise’) that biases the non-local reading. The verbs were initially selected based on native-speaker judgment, but the verbs’ self- vs. other-directed biases were confirmed in Experiment 1a. We used ziji in possessive position (ziji de in (8)) because this is the most frequent grammatical position in which ziji occurs (in the Lancaster Corpus of Mandarin Chinese; Jia, 2020).

Half of the local and non-local antecedents were male, and half were female. Ten different verbs (‘notice’, ‘hear’, ‘say’, etc.) were used as the matrix verb in the critical sentence. Twenty sets of target items were created and distributed into 4 lists in a Latin Square design. Thus, each participant only saw a particular item once, and saw 5 targets in each of the 4 conditions over the course of the experiment. In the self-paced reading Experiment 1b, the critical region is the reflexive ziji, preceded by the biased verb and followed by three spillover regions: DE, a modifier, and an NP.

Twenty fillers were interleaved with targets such that each target was followed or preceded by a filler. The fillers all contained non-reflexive pronouns. On filler trials in Experiments 1a and 1b, comprehension questions asked about the non-reflexive pronoun to ensure that participants paid attention.

4.2 Experiment 1a: Forced-choice judgment

4.2.5 Results

Figure 1 shows participants’ mean preference of selecting the local referent as the antecedent of ziji. For statistical analysis, see Table 1. The mixed-effect logistic model indicates a main effect of verb bias (p < 0.001). As Figure 1 shows, when the verb is self-directed, participants preferred local NPs as antecedents (63% in the biased context and 82% in the neutral context), but when the verb is other-directed, they overwhelmingly chose non-local NPs (85% in the biased context and 77% in the neutral context). Context modulates participants’ choices as well, as critical sentences preceded by biased contexts made participants less likely to select local NPs as antecedents (p < 0.001). There is no significant context x verb bias interaction.

Figure 1: Mean percentages of local coreference in Experiment 1a on ziji.

Table 1: Summary of statistics for Experiment 1a (*: <0.05).

	β	SE	t-value	p-value
Context	–0.92	0.18	–5.01	<0.001*
Verb	–3.01	0.21	–14.67	<0.001*
Context x Verb	0.35	0.36	0.97	0.33

Model structure: glmer(Answer ~ Context * Verb + (1|Subject_ID) + (1|Item_ID), data, family = binomial).

Overall, these patterns suggest that (i) the verb bias manipulation is effective: self-directed and other-directed verbs guide the interpretation of ziji in expected directions, and (ii) discourse-level information modulates Chinese speakers’ antecedent choices: participants are more likely to select the non-local referent when it is a discourse topic. In other words, these two kinds of non-structural cues influence participants’ offline antecedent choices for ziji. Next, we turn to Experiment 1b to assess the Syntactic Filter Hypothesis and the Multiple Constraints Hypothesis.

4.3 Experiment 1b: Self-paced reading

4.3.5 Results

The reading times are in Figure 2. The critical region is Region 7, ziji. Visually, it’s clear that, first, words in biased context conditions are processed faster compared to the neutral contexts. Second, verb-related differences within each context type appear at the verb, prior to the reflexive ziji. At the reflexive itself, RTs are faster in biased contexts than in neutral contexts, but there appears to be no effect of verb bias.

Figure 2: Mean RTs (ms) across regions in the target sentence in Experiment 1b.

These observations are confirmed by statistical analysis (Table 2).³ First, the context main effect is significant across all regions except Region 1 (ps < 0.005), showing that target sentences preceded by biased contexts were read faster. This is not relevant for our main claims and is expected under a perspective-shift account.

Table 2: Summary of statistics for log-transformed RTs in Experiment 1b (*: <0.05).

Region	Context				Verb				Context x Verb
	β	SE	t-value	p-value	β	SE	t-value	p-value	β	SE	t-value	p-value
In meeting	0.01	0.02	0.67	0.50	0.005	0.02	0.29	0.77	0.03	0.03	0.77	0.44
chairman/he	0.08	0.02	4.34	<0.001*	–0.03	0.02	–1.72	0.09	–0.06	0.03	–1.76	0.08
noticed	0.12	0.03	4.88	<0.001*	0.03	0.02	1.61	0.13	0.02	0.03	0.67	0.50
Director Li	0.11	0.02	5.99	<0.001*	–0.001	0.02	–0.07	0.94	–0.0001	0.04	–0.002	0.99
constantly	0.07	0.02	3.84	<0.001*	–0.01	0.02	–0.72	0.47	0.03	0.04	0.74	0.46
verbed	0.06	0.02	2.72	0.01*	–0.02	0.02	–0.84	0.40	–0.12	0.03	–3.73	<0.001*
ziji	0.08	0.01	5.39	<0.001*	0.002	0.01	0.02	0.87	–0.02	0.03	–0.53	0.60
DE	0.05	0.01	4.20	<0.001*	0.008	0.01	0.65	0.51	–0.005	0.02	–0.21	0.84
management	0.06	0.01	4.34	<0.001*	–0.03	0.01	–1.79	0.07	–0.03	0.03	–0.98	0.32
skills	0.08	0.02	3.12	0.002*	0.01	0.02	0.46	0.64	0.03	0.05	0.53	0.60

The final models for the biased verb, reflexive, and post-reflexive regions are as follows: Verb region: lmer(logRT ~ Context * Verb + (1 + Context + Verb|Subject_ID) + (1 + Context|Item_ID), data). Reflexive region: lmer(logRT ~ Context * Verb + (1|Subject_ID) + (1|Item_ID), data). Post-reflexive region: lmer(logRT ~ Context * Verb + (1|Subject_ID) + (1|Item_ID), data).

At the verb region, in addition to the context main effect (p < 0.001; raw RT analysis: β = 37.08, SE = 8.68, t = 4.27, p < 0.001), we found a context x verb bias interaction (p < 0.001; raw RT analysis: β = –76.02, SE = 17.34, t = –4.38, p < 0.001). This shows that verb bias has different effects in neutral and biased contexts. Pairwise comparisons revealed that in neutral contexts, other-directed verbs lead to RT slowdowns relative to self-directed verbs (log-transformed RT analysis: β = –0.08, SE = 0.02, t = –3.08, p = 0.002; raw RT analysis: β = –56.56, SE = 14.44, t = –3.92, p < 0.001). This is predicted by both the Syntactic Filter Hypothesis and the Multiple Constraints Hypothesis (given prior work showing that reflexive-related effects can occur on the preceding verb). However, in the biased context, self-directed verbs caused longer RTs than other-directed verbs (log-transformed RT analysis: β = 0.0, SE = 0.02, t = 2.13, p = 0.03; raw RT analysis: β = 20.75, SE = 9.37, t = 2.21, p = 0.03). This is the opposite of what the Syntactic Filter Hypothesis predicts and fits better with the Multiple Constraints Hypothesis.

For the critical region ziji and the three spillover regions, we only found main effects of context (ps < 0.001) in the log-transformed RT analysis. However, analysis of raw RTs for the second spillover region (‘management’) reveals a main effect of verb bias (β = –21.27, SE = 8.08, t = –2.63, p < 0.01) and a marginal context x verb bias interaction (β = –28.25, SE = 16.08, t = –1.76, p = 0.08). Pairwise comparisons indicate that while there is no verb bias effect in biased contexts (β = –6.11, SE = 7.56, t = –0.81, p = 0.42), other-directed verbs lead to slowdowns in neutral contexts (β = –36.69, SE = 14.04, t = –2.61, p < 0.01), pointing to a locality bias. No other effects at the spillover regions are significant.

5.1 Materials and design for Experiments 2a and 2b

The materials used in Experiment 2 are identical to Experiment 1, except ziji was replaced by ta-ziji.

5.2 Experiment 2a: Forced-choice judgment

5.2.5 Results

As can be seen in Figure 3, participants’ antecedent choices are modulated by verb bias as well as context. See Table 3 for statistics. Participants preferred non-local binding when the verb is other-directed (Biased context: 81%; Neutral context: 75%) and local binding when the verb is self-directed (Biased context: 77%; Neutral context: 82%). Therefore, we found different antecedent choice results than Lu (2011) regarding ta-ziji. (We come back to this in the discussion.) Instead, we find – in line with our Experiment 1a on ziji – that verb bias is a stronger cue in offline judgment than syntactic locality in guiding antecedent choices with ta-ziji. The context main effect is also significant (p < 0.05). This novel finding indicates that the previous claim that ta-ziji is sensitive to antecedent prominence (Pan, 1998; Pan & Hu, 2002) seems applicable to the discourse level. If the non-local antecedent is the discourse topic and thus more prominent, LD binding is more accessible, relative to when the non-local antecedent is not a discourse topic.

Figure 3: Mean percentages of local coreference in Experiment 2a.

Table 3: Summary of statistics for Experiment 2a (*: <0.05).

	β	SE	t-value	p-value
Context	–0.42	0.18	–2.38	0.017*
Verb	–3.13	0.20	–15.34	<0.001*
Context x Verb	–0.26	0.35	0.46	0.46

Model structure: glmer(Answer ~ Context * Verb + (1|Subject_ID) + (1|Item_ID), data, family = binomial).

5.3 Experiment 2b: Self-paced reading

5.3.5 Results

The reading times are in Figure 4. The critical region is Region 7, ta-ziji. As we will see below, in contrast to Experiment 1b, we found no effects on the verb,⁵ and thus we focus on the reflexive region. Before the critical region, the main effect of verb bias reaches significance at the matrix subject (e.g. ‘chairman/he’) and the embedded subject (‘Director Li’), respectively (ps < 0.05). We believe these effects are spurious because the biased verbs have not yet been encountered.

Figure 4: Mean RTs (ms) across regions in the target sentence in Experiment 2b.

There are three major findings. First, as predicted, there is a context main effect in all regions except Region 1 (ps < 0.001, see Table 5). Second, at ta-ziji, other-directed verb conditions are read more slowly than self-directed verb conditions (main effect of verb bias, p < 0.001; raw RT analysis: β = –38.51, SE = 9.20, t = –4.19, p < 0.001), but this is modulated by a context x verb bias interaction that reaches marginal significance in the log-transformed RT analysis (p = 0.08) and significance in the raw RT analysis (β = –49.33, SE = 18.55, t = –2.66, p < 0.01). Pairwise comparisons in log-transformed RT analysis and in raw RT analysis show that self-directed and other-directed verbs differ in the neutral context as RTs are longer for other-directed verbs (log-transformed RT analysis: β = –0.09, SE = 0.02, t = –3.99, p < 0.001; raw RT analysis: β = –64.45, SE = 14.66, t = –4.40, p < 0.001), but not in the biased context (log-transformed RT analysis: β = –0.04, SE = 0.02, t = –1.61, p = 0.11; raw RT analysis: β = –13.31, SE = 11.06, t = –1.20, p = 0.23). The finding that, in the neutral context, other-directed verbs elicited longer RTs than self-directed verbs replicates Experiment 1b at the verb. However, in contrast to Experiment 1b, we found no differences between self- and other-directed verbs in the biased contexts with discourse topics, suggesting local and non-local binding are equally probable to participants in real-time parsing.

Table 5: Summary of statistics for RTs in Experiment 2b (*: <0.05).

Region	Context				Verb				Context x Verb
	β	SE	t-value	p-value	β	SE	t-value	p-value	β	SE	t-value	p-value
In meeting	0.02	0.02	1.10	0.27	0.0005	0.02	0.034	0.97	–0.049	0.03	–1.54	0.12
chairman/he	0.08	0.02	5.02	<0.001*	–0.04	0.02	–2.21	0.03*	0.016	0.03	0.47	0.64
noticed	0.13	0.02	8.50	<0.001*	0.002	0.02	0.14	0.89	–0.009	0.03	–0.28	0.77
Director Li	0.12	0.02	7.11	<0.001*	–0.05	0.02	–2.81	0.005*	–0.02	0.03	–0.46	0.65
constantly	0.07	0.02	3.99	<0.001*	–0.004	0.02	–0.26	0.80	–0.004	0.03	–0.12	0.92
verbed	0.09	0.02	5.29	<0.001*	–0.03	0.02	–1.70	0.09	–0.04	0.03	–1.19	0.23
ta-ziji	0.10	0.02	5.92	<0.001*	–0.06	0.02	–3.93	<0.001*	–0.06	0.03	–1.74	0.08
DE	0.05	0.01	3.53	<0.001*	–0.03	0.01	–2.32	0.02*	–0.02	0.03	–0.70	0.49
management	0.04	0.01	3.01	0.003*	–0.005	0.01	–0.38	0.70	–0.07	0.03	–2.85	0.005*
skills	0.09	0.03	3.50	<0.001*	–0.08	0.03	–2.87	0.005*	–0.1	0.05	–1.83	0.07

The final models for the biased verb, reflexive, and post-reflexive regions are as follows: Verb region: lmer(logRT ~ Context * Verb + (1|Subject_ID) + (1|Item_ID), data). Reflexive region: lmer(logRT ~ Context * Verb + (1 + Context +Verb|Subject_ID) + (1|Item_ID), data). Post-reflexive region: lmer(logRT ~ Context * Verb + (1 + Context|Subject_ID) + (1|Item_ID), data).

Finally, the verb bias effect in neutral contexts carries over to the spillover regions. In log-transformed RT analyses, the context x verb bias interaction reaches significance at region 9 (‘management’, p = 0.005) while in raw RT analyses, the interaction is significant at both region 9 (‘management’) (β = –41.25, SE = 12.45, t = –3.31, p < 0.001) and region 10 (‘skills’) (β = –122.99, SE = 52.79, t = –2.33, p < 0.05). Pairwise comparisons in log-transformed RT analyses suggest that for both regions, other-directed verbs caused reading slowdowns in the neutral context only (Region 9: β = –0.04, SE = 0.02, t= –2.22, p < 0.05; Region 10: β = –0.12, SE = 0.04, t = –3.19, p = 0.001), which matches the raw RT analyses (Region 9: β = –24.52, SE = 9.51, t = –2.58, p = 0.01; Region 10: β = –144.47, SE = 39.18, t = –3.69, p < 0.001).

6.1 Summary of results

This work has two main goals. The linguistic goal is to test whether ta-ziji is sensitive to (i) verb bias semantics and (ii) discourse topic prominence, like ziji. Gaining knowledge about these fundamental linguistic patterns is meaningful from a linguistic perspective and also lays the foundation for evaluating sentence processing hypotheses. Our psycholinguistic goal is to examine the effects of non-syntactic constraints on the processing of ziji and ta-ziji in discourse, to evaluate the Syntactic Filter Hypothesis and the Multiple Constraints Hypothesis. By comparing ziji and ta-ziji, we can also assess whether the offline and online processing patterns of these two reflexive forms are different.

We created local and non-local semantic dependencies by manipulating verb directedness. In neutral contexts where neither of the antecedents is mentioned prior to the critical sentence, a tension between verb semantics and the locality constraint is created when the verb is other-directed. This manipulation allows us to replicate the previous finding that ziji and ta-ziji are both subject to a locality constraint despite the option of LD binding for ziji (e.g. Dillon et al., 2016; Gao et al., 2005; Jäger et al., 2015; Lyu et al., 2022; Wang, 2017a). The two biased verb conditions in neutral contexts also serve as a baseline for the conditions in biased contexts, where the non-local antecedent is a discourse topic. Any change in the processing pattern should thus be ascribed to the change of the context. The Syntactic Filter Hypothesis predicts a main effect of verb bias in neutral and biased contexts for ziji and ta-ziji, but the Multiple Constraints Hypothesis predicts a context x verb bias interaction for these two forms.

Experiment 1 investigated the interpretation of ziji. In the forced-choice Experiment 1a, Chinese speakers clearly preferred antecedents congruent with verb semantics: when the verb is self-directed, they preferred local dependencies; when the verb is other-directed, they preferred non-local dependencies. Moreover, biased contexts made Chinese speakers more likely to consider the non-local antecedent which is a discourse-topic, relative to neutral contexts where no antecedent is topically prominent. This finding fits with prior claims that one tends to take the perspective of a discourse topic (Kuno, 1987) and that ziji is perspective-sensitive (e.g. Charnavel et al., 2017; Huang & Liu, 2001; Huang et al., 2009; Pan, 1997; 2001; Wang & Pan, 2015).

Experiment 1b (self-paced reading) investigated the processing of ziji. At the embedded verb, we observe that, in the neutral context, participants showed reading slowdowns when the verb is other-directed. In contrast, in the biased context, the pattern flipped, because now self-directed verbs elicited reading slowdowns. (As discussed earlier, this effect at the verb region is also seen in prior work and potentially related to participants’ anticipatory processing behavior; online processing is known to be highly anticipatory.) Critical for our purposes, the context x verb bias interaction supports the Multiple Constraints Hypothesis but not the Syntactic Filter Hypothesis.

Experiment 2 explored similar issues in the processing of the complex reflexive ta-ziji to assess whether ta-ziji is strictly local in offline and real-time interpretations. In the forced-choice Experiment 2a, participants again based anaphoric interpretations on verb bias semantics: they mostly chose local antecedents when the verb is self-directed and non-local antecedents when the verb is other-directed. Intriguingly, participants preferred non-local readings of ta-ziji more in biased contexts than in neutral contexts, suggesting that topic prominence indeed impacts the processing of ta-ziji. Nevertheless, this main effect of context is weaker than what has been found for ziji, attributable to the different linguistic properties of ziji and ta-ziji. These kinds of form-specific asymmetries have also been observed in other languages (see e.g. Kaiser & Trueswell, 2008, Kaiser et al., 2009 on form-specific effects).

Experiment 2b (self-paced reading) found immediate sensitivity to both verb bias and discourse structure with ta-ziji. In the neutral context, the critical region ta-ziji was read more slowly when the preceding verb was other-directed as opposed to self-directed. This is expected due to the clash of verb bias and the locality constraint. In the biased context, no processing differences were observed between the two verb types, suggesting that local and non-local readings were equally probable in real-time reference resolution. The absence of a verb bias effect with ta-ziji in biased contexts contrasts with the verb bias observed with ziji. These findings fit with our suggestion that topic prominence may have a stronger influence on ziji than ta-ziji. At any rate, the context x verb bias interaction at the reflexive ta-ziji (significant in the raw RT analysis, marginal in the log-RT analysis) is consistent with the predictions of the Multiple Constraints Hypothesis, and echoes what we found with ziji.

Taken together, our results suggest that Chinese speakers recruit multiple sources of information – structural and non-structural – at early stages of reference resolution. However, the offline data suggest that, over time, discourse-level and syntactic constraints may decay, as participants largely based their sentence-final antecedent choices on verb semantics. Another important finding is that discourse topicality seems to impact the processing of ziji and ta-ziji differently. We discuss the broader implications of our findings below.

6.2 Long-distance binding of ta-ziji

Regarding ta-ziji, we found that this form is sensitive to verb semantics and topic prominence. These findings have implications for linguistic theories.

When verb semantics biases non-local antecedents (e.g. ‘flatter’), Chinese speakers strongly preferred non-local antecedents with ta-ziji in Experiment 2a. This novel finding seems inconsistent with Lu (2011), who found that local readings were strongly preferred with ta-ziji when context-dependent verb bias information (e.g. ‘delivering’ biasing non-local ‘mailman’) conflicts with the locality constraint. This difference may stem from the different aspects of the verb information being tested. Consequently, the impact of verb semantics in our study is stronger than the context-dependent verb effects in Lu (2011).

Another key finding is that topic prominence impacts the offline and online resolution of ta-ziji, similar to what we see with ziji. Construed superficially, this means that the Prominence Constraint (Pan, 1998; Pan & Hu, 2002) should include topic prominence, in addition to grammatical prominence and animacy prominence. But perhaps more importantly, the fact that local and non-local readings in biased contexts are equally probable in Experiment 2b suggests that LD binding of ta-ziji (an “exempt” reading) was considered by participants even if the local antecedent is a viable animate binder. This finding may seem surprising, especially given the linguistic behavior of exempt anaphors in languages like English, where local binding is preferred when an animate referent is available in the local domain (see picture NP reflexives in Cunnings & Sturt, 2014).

Traditionally, it has been suggested that in English, syntactic reflexives subject to Principle A and exempt reflexives licensed extra-syntactically are in complementary distribution (Pollard & Sag, 1992; Reinhart & Reuland, 1991; 1993). Under this view, the exempt LD reading of himself in John said that the newspaper published a picture of himself is allowed because the reflexive does not have an animate clausemate antecedent. But if himself has a viable clausemate antecedent, some claim that it must be locally bound. This is summarized by Reuland’s (2001; 2011) Rule L: when a viable local antecedent exists, an exempt reading is impossible, as this kind of extra-syntactic reading is computationally more costly.

However, given our finding that LD binding of ta-ziji in biased contexts is possible and that LD binding does not lead to extra processing effort relative to local binding, a categorical Rule L seems too strong. Indeed, even prior work on English reflexives (Kaiser et al., 2009; Runner et al., 2006) and on the Korean complex reflexive caki-casin (Kim & Yoon, 2020) indicates that exempt readings are possible when the local antecedent is animate. In fact, in an unpublished study (Lyu & Kaiser, 2023), we found that logophoric properties of non-local antecedents – source vs. perceiver status (see e.g. Culy, 1994; Kaiser, 2022; Kaiser et al., 2009; Sloggett, 2017) – impact the online and offline interpretation of ta-ziji, further indicating that exempt reflexives (e.g. ta-ziji) are not necessarily in complementary distribution with syntactic reflexives.

As a whole, our findings suggest that, to capture the behavior of ta-ziji, we may want to extend Pan and Hu’s (2002) claims about prominence, so that semantic, syntactic, and discourse-pragmatic prominence can all impact LD binding of ta-ziji. However, instead of a monolithic prominence constraint outranking locality, we hypothesize that different types of prominence should be considered separately, and suggest that with ta-ziji, discourse topic prominence competes with, but does not outrank, syntactic locality.

6.3 Towards a unification of modular and constraint-based approaches

Now we turn to some of the broader implications from a psycholinguistic perspective. We interpret the self-paced reading results as supporting the Multiple Constraints Hypothesis.⁶ However, other studies present evidence that sometimes syntactic cues are accessed first, before non-structural cues (e.g. animacy, gender), supporting a modular account (e.g. Chang et al., 2020; Cunnings & Sturt, 2014; Nicol & Swinney, 1989; Sturt, 2003). In this section, we explore whether these results can be reconciled.

Support for the Syntactic Filter Hypothesis largely comes from work on the Binding Theory and c-command (e.g. Felser & Cunnings, 2012; Kazanina et al., 2007; Kush et al., 2015; Sturt, 2003). Conceivably, these constraints are “hard,” as opposed to “soft” constraints (see e.g. Kush et al., 2017; Felser & Drummer, 2017). This distinction is extensively used in natural language processing (e.g. Eisner & Smith, 2010) and has also been used to characterize human sentence processing (e.g. Cunnings et al., 2014; Dillon et al., 2013). While there is no clear consensus on whether “hard” constraints are inviolable or merely very highly-ranked/heavily-weighted, the basic intuition is that there are (at least) two kinds of constraints: hard constraints, whose violation incurs steep penalties and which may even be inviolable, and soft constraints, which have lower weights but whose violation still incurs a penalty (see e.g. Cunnings et al., 2014; Dillon et al., 2013; Parker & Phillips, 2017, for discussion).

The distinction between hard and soft constraints is supported by prior work. For example, Kush et al. (2017) showed that in a strong crossover configuration (9a) which involves a potential violation of Principle C (a hard constraint), structurally inaccessible distractors (here, ‘maintenance man’) have no effect on pronoun resolution (as predicted by the Syntactic Filter Hypothesis). This fits with Principle C being a hard constraint, strong enough to block the distractor. Now consider a weak crossover configuration (ex.9b). Here, Principle C is irrelevant and only the weak crossover constraint, hypothesized to be a soft constraint, is at play. Now, the distractor does interfere with pronoun processing, contrary to the Syntactic Filter Hypothesis. In sum, this difference is captured if Principle C is a hard constraint, and the weak crossover constraint is a soft one. This suggests that the Syntactic Filter Hypothesis can predict the behavior of hard constraints but not soft constraints.

We suggest that the locality, semantic and topic prominence constraints that we tested are soft constraints (though probably with somewhat different weights), and thus do not pattern as predicted by the Syntactic Filter Hypothesis and instead fit better with the Multiple Constraints Hypothesis. Our findings thus open the door for future investigations that more systematically compare the interaction of constraints with varying weights.

Another question we leave for future work is how the hard vs. soft distinction should be modeled in accounts of language processing. There are (at least) two ways. One is using a rank-based system like the classical OT (Kager, 1999; Prince & Smolensky, 1993) or stochastic OT (Boersma, 1997; Boersma & Hayes, 2001). On this view, hard constraints (e.g. hard structural constraints) would be ranked above other constraints (e.g. non-structural constraints) à la Stevenson and Smolensky (2006). Alternatively, we could adopt a weight-sensitive system similar to Harmonic Grammar (e.g. Pater, 2009; Potts et al., 2010), the spirit of which is found in the work of Parker and Phillips (2017). Here, hard constraints would be assigned more weight than soft constraints, assuming that language comprehenders do not lose attention, use shallow parsing strategies (Barton & Sanford, 1993; Ferreira et al., 2002), or confuse structural and semantic cues (Jäger et al., 2015).

However, unifying multiple-constraint approaches and modular approaches is not without challenges. Even if we distinguish hard vs. soft structural constraints, there is still no consensus whether hard constraints (e.g. Principles A and C) are prioritized in early-stage processing (see e.g. Dillon, 2014; Drummer & Felser, 2018; Jäger et al., 2020; Kaiser et al., 2009; Patil et al., 2016; Runner et al., 2006). These divergent findings may stem from methodological differences or from statistical power (see e.g. Jäger et al., 2020; Patil et al., 2016 for discussion). Therefore, although unifying the modular account and the multiple constraints account is conceivable, we first need a better understanding of the nature of these constraints and more empirical evidence. We regard this as a valuable direction for future work.