In the processing of subject-verb agreement, non-subject plural nouns following a singular subject sometimes “attract” the agreement with the verb, despite not being grammatically licensed to do so. This phenomenon generates agreement errors in production and an increased tendency to fail to notice such errors in comprehension, thereby providing a window into the representation of grammatical number in working memory during sentence processing. Research in this topic, however, is primarily done in related languages with similar agreement systems. In order to (...) increase the cross-linguistic coverage of the processing of agreement, we conducted a self-paced reading study in Modern Standard Arabic. We report robust agreement attraction errors in relative clauses, a configuration not particularly conducive to the generation of such errors for all possible lexicalizations. In particular, we examined the speed with which readers retrieve a subject controller for both grammatical and ungrammatical agreeing verbs in sentences where verbs are preceded by two NPs, one of which is a local non-subject NP that can act as a distractor for the successful resolution of subject-verb agreement. Our results suggest that the frequency of errors is modulated by the kind of plural formation strategy used on the attractor noun: nouns which form plurals by suffixation condition high rates of attraction, whereas nouns which form their plurals by internal vowel change (ablaut) generate lower rates of errors and reading-time attraction effects of smaller magnitudes. Furthermore, we show some evidence that these agreement attraction effects are mostly contained in the right tail of reaction time distributions. We also present modeling data in the ACT-R framework which supports a view of these ablauting patterns wherein they are differentially specified for number and evaluate the consequences of possible representations for theories of grammar and parsing. (shrink)

We present computational modeling results based on a self‐paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k‐fold cross‐validation. We find that our data are better accounted for by an encoding‐based model of agreement attraction, compared to a retrieval‐based model. A novel methodological contribution of our study is the use of comprehension questions with open‐ended responses, so that (...) both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model. (shrink)

Previous work on the comprehension of agreement has shown that incorrectly inflected verbs do not trigger responses typically seen with fully ungrammatical verbs when the preceding sentential context furnishes a possibly matching distractor noun (i.e., agreement attraction). We report eight studies, three being direct replications, designed to assess the degree of similarity of these errors in the comprehension of subject-verb agreement along the dimensions of grammatical gender and number in Modern Standard Arabic. A meta-analysis of the results demonstrate the presence (...) of agreement attraction effects in reading comprehension for gender and number on verbs. Moreover, the meta-analysis demonstrates that these two features do not behave identically: gender effects are larger and occur later relative to number attraction effects. These results challenge models of agreement that predict agreement features to be equipotent and show that real-time models of agreement require modifications in the form of cue-weighting in order to account for these differential results. (shrink)

We present a self-organizing approach to sentence processing that sheds new light on notional plurality effects in agreement attraction, using pseudopartitive subject noun phrases. We first show that notional plurality ratings predict verb agreement choices in pseudopartitives, in line with the “Marking” component of the Marking and Morphing theory of agreement processing. However, no account to date has derived notional plurality values from independently needed principles of language processing. We argue on the basis of new experimental evidence and a dynamical (...) systems model that the theoretical black box of notional plurality can be unpacked into objectively measurable semantic features. With these semantic features driving structure formation, our model reproduces the human verb production patterns as a byproduct of normal processing. Finally, we discuss how the self-organizing approach might be extended to other agreement attraction phenomena. (shrink)

Cognitive Science, Volume 46, Issue 2, February 2022.

Agreement attraction is a cross-linguistic phenomenon where a verb occasionally agrees not with its subject, as required by grammar, but instead with an unrelated noun (“The key to the cabinets were…”). Despite the clear violation of grammatical rules, comprehenders often rate these sentences as acceptable. Contenders for explaining agreement attraction fall into two broad classes: Morphosyntactic accounts specifically designed to explain agreement attraction, and more general sentence processing models, such as the Lewis and Vasishth model, which explain attraction as a (...) consequence of how linguistic structure is stored and accessed in content-addressable memory. In the present research, we disambiguate between these two classes by testing a surprising prediction made by the Lewis and Vasishth model but not by the morphosyntactic accounts, namely, that attraction should not be limited to morphosyntax, but that semantic features of unrelated nouns equally induce attraction. A recent study by Cunnings and Sturt provided initial evidence that this may be the case. Here, we report three single-trial experiments in English that compared semantic and agreement attraction and tested whether and how the two interact. All three experiments showed strong semantically induced attraction effects closely mirroring agreement attraction effects. We complement these results with computational simulations which confirmed that the Lewis and Vasishth model can faithfully reproduce the observed results. In sum, our findings suggest that attraction is a more general phenomenon than is commonly believed, and therefore favor more general sentence processing models, such as the Lewis and Vasishth model. (shrink)

One of the central questions in second language processing studies is whether native and second language readers process sentences relying on the same mechanisms or there are qualitative differences. As their proficiency grows, L2 readers become more efficient, but it is difficult to determine whether they develop native-like mechanisms or rely on different strategies. Our study contributes to this debate by focusing on constructions that were demonstrated to cause characteristic problems in L1 processing: a particular type of case errors in (...) Russian was taken as an example. We investigated how beginner and intermediate learners of Russian process such errors, measuring reading times and grammaticality judgment accuracy. At the beginner level, we found non-native-like patterns both in online and in offline measures. But at the intermediate level, native-like problems emerged in offline measures. In our view, this is a strong indication that these readers are using the same underlying mechanisms as in L1 processing. In online measures, L2 readers at both levels were, in general, much slower than native participants and exhibited characteristic non-native-like patterns, which we explained by delayed morphosyntactic processing. We conclude that our results are compatible with approaches, assuming that the mechanisms for L1 and advanced L2 processing are the same, but L2 processing is more cognitively demanding and therefore slower. (shrink)

Cognitive Science, Volume 46, Issue 2, February 2022.