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When comprehenders predict a specific lexical noun in a highly constraining context, they also activate the grammatical features, such as gender, of that noun. Evidence for such lexically mediated prediction comes from ERP studies that show that comprehenders are surprised by adjectives and determiners that mismatch the features of a highly predictable noun. In this study, we investigated whether comprehenders can (i) predict an abstract noun phrase in an upcoming argument position (without pre-activating a specific lexical item) and (ii) assign morphosyntactic features to the head noun of that phrase. To do so we used the processing of Dutch cataphors as a test case. We tested whether seeing a cataphor in a preposed clause triggered a prediction of a feature-matching antecedent NP in main subject position. If comprehenders predicted a feature-matching subject, we reasoned that they should also expect an agreeing main verb, which comes before the subject because Dutch is a V2 language. A single-word prediction experiment showed that comprehenders expect a main verb matching the number of the cataphor. In a follow-up self-paced reading experiment, we found a number-mismatch effect if the V2 main verb did not agree with the cataphor. We take the results as evidence that comprehenders predicted a matching antecedent in subject position. We argue that the results are better explained as involving prediction of an abstract noun phrase marked for morphological features, rather than a specific lexical item.

One of the key features of natural languages is that they exhibit long-distance filler-gap dependencies (FGDs): In the sentence `What do you think the pilot sent __?' the wh-filler what is interpreted as the object of the verb sent across multiple words. The ability to establish FGDs is thought to require hierarchical syntactic structure. However, recent research suggests that recurrent neural networks (RNNs) without specific hierarchical bias can learn complex generalizations about wh-questions in English from raw text data (Wilcox et al. 2018; 2019). Across two experiments, we probe the generality of this result by testing whether a long short-term memory (LSTM) RNN model can learn basic generalizations about FGDs in Norwegian. Testing Norwegian allows us to assess whether previous results were due to distributional statistics of the English input or whether models can extract similar generalizations in languages with different syntactic distributions. We also test the model's performance on two different FGDs: wh-questions and relative clauses, allowing us to determine if the model learns abstract generalizations about FGDs that extend beyond a single construction type. Results from Experiment 1 suggest that the model expects fillers to be paired with gaps and that this expectation generalizes across different syntactic positions. Results from Experiment 2 suggest that the model's expectations are largely unaffected by the increased linear distance between the filler and the gap. Our findings provide support for the conclusion that LSTM RNN's ability to learn basic generalizations about FGDs is robust across dependency type and language.

Norwegian allows filler-gap dependencies into embedded questions, which are islands for filler-gap dependency formation in English. We ask whether there is evidence that Norwegian learners of English transfer the functional structure that permits island violations from their first language (L1) to their second language (L2). In two acceptability judgment studies, we find that Norwegians are more likely to accept 'island-violating' filler-gap dependencies in L2 English if the corresponding filler-gap dependency is acceptable in Norwegian: Norwegian learners variably accept English sentences with dependencies into embedded questions, but not into subject phrases. These results are consistent with models that permit transfer of abstract functional structure. Norwegians are still less likely to accept filler-gap dependencies into English embedded questions than Norwegian embedded questions. We interpret the latter finding as evidence that, despite transfer, Norwegian speakers may partially restructure their L2 English analysis. We discuss how indirect positive evidence may play a role in helping learners restructure.

This article investigates how children acquire word order generalizations from ambiguous and infrequent input. We focus on verb placement in Norwegian relative and complement clauses. In two elicitation experiments we explore where children (age 3-7) place verbs in three embedded clauses types: one requiring a purely syntactic generalization and two requiring a semantic-pragmatic generalization. We find that children overgeneralize the main clause word order to embedded clauses. However, this happens with different probabilities across all three clause types. We take this to mean that children overgeneralize and that they entertain both coarse and fine-grained hypotheses simultaneously. We also suggest that children make use of frequency information, both in making initial hypotheses and when retracting from overgeneralization.

It is often reported that embedded questions (EQs) are not syntactic islands in Spanish. However, some authors have observed that the acceptability of filler-gap dependencies (FGDs) into Spanish EQs varies with the EQ-embedding verb: FGDs into EQs under responsive verbs (e.g., know) do not result in island effects, but FGDs into EQs under rogative verbs (e.g., ask) do yield island effects. One account attributes the contrast to a structural difference between the two EQs, due to which ask-EQs violate Bounding constraints, but know-EQs do not. In two acceptability studies we investigated the reliability of verb-dependent island effects in EQs introduced by si ‘whether’ and cuándo ‘when’. We found no qualitative acceptability differences between ask and know EQ-island sentences, suggesting that the syntactic islandhood of Spanish EQs is not verb-dependent. Nevertheless, average island effects were numerically greater with ask, suggesting the presence of a non-syntactic constraint. In addition, FGDs into whether-EQs were generally acceptable, whereas FGDs into when-EQs obtained unacceptable average ratings and highly variable judgments. We argue that in neither case there is a Bounding constraint violation. Instead we explore alternative potential explanations for the differences in terms of features, presuppositions and processing pressures.

Past studies have shown that antecedent prominence affects the processing of a pronoun, but these studies have used experimental methodologies that do not make it possible to determine at what stage(s) of pronominal resolution these effects occur. We used the speed-accuracy tradeoff procedure to investigate whether antecedent prominence affects the accuracy of antecedent retrieval, the speed of resolution, or both. Consistent with previous results, we find that accuracy is higher when antecedents are prominent than when they are not (cf. Foraker & McElree, 2007). However, in contrast to previous results, we also find that prominence impacts the speed with which the pronominal dependency is resolved. We consider the implications of our findings for various models of pronoun resolution and offer suggestions for how to implement prominence-sensitive speed differences within a cue-based retrieval architecture.

Filler‐gap dependency resolution is often characterized as an active process. We probed the mechanisms that determine where and why comprehenders posit gaps during incremental processing using Norwegian as our test language. First, we investigated why active filler‐gap dependency resolution is suspended inside island domains like embedded questions in some languages. Processing‐based accounts hold that resource limitations prevent gap‐filling in embedded questions across languages, while grammar‐based accounts predict that active gap‐filling is only blocked in languages where embedded questions are grammatical islands. In a self‐paced reading study, we find that Norwegian participants exhibit filled‐gap effects inside embedded questions, which are not islands in the language. The findings are consistent with grammar‐based, but not processing, accounts. Second, we asked if active filler‐gap processing can be understood as a special case of probabilistic ambiguity resolution within an expectation‐based framework. To do so, we tested whether word‐by‐word surprisal values from a neural language model could predict the location and magnitude of filled‐gap effects in our behavioral data. We find that surprisal accurately tracks the location of filled‐gap effects but severely underestimates their magnitude. This suggests either that mechanisms above and beyond probabilistic ambiguity resolution are required to fully explain active gap‐filling behavior or that surprisal values derived from long‐short term memory are not good proxies for humans' incremental expectations during filler‐gap resolution. [ABSTRACT FROM AUTHOR]

Embedded questions (EQs) are islands for filler–gap dependency formation in English, but not in Norwegian. Kush and Dahl (2022) found that first language (L1) Norwegian participants often accepted filler–gap dependencies into EQs in second language (L2) English, and proposed that this reflected persistent transfer from Norwegian of the functional structure that licenses such filler–gap dependencies. However, their results do not conclusively establish that the judgment patterns were specific to transfer from L1 Norwegian and not a general L2 effect. To address this issue, we conducted elicited production tasks comparing how L1 Norwegian and L1 Swedish speakers complete dependencies into declarative complement clauses and EQs both in their native languages and L2 English. Despite its similarity to Norwegian, Swedish prohibits the filler–gap dependency into EQs that Norwegian allows. We expected participants to complete dependencies that they considered grammatical with gaps and to avoid gaps where they considered them ungrammatical. Our results clearly indicate transfer: L1 Norwegian participants overwhelmingly used gaps when completing dependencies into EQs in both L1 and L2, whereas Swedish participants almost never used gaps in either language. We interpret our results as support for models that allow transfer of functional heads and their associated features from L1 to L2, and suggest that such transfer persists when the L2 input does not provide relevant evidence for restructuring. [ABSTRACT FROM AUTHOR]

Finite adjunct clauses are often assumed to be among the strongest islands for filler–gap dependency creation cross-linguistically, but Kush, Lohndal & Sprouse (2019) found experimental evidence suggesting that finite conditional om-adjunct clauses are not islands for topicalization in Norwegian. To investigate the generality of these findings, we ran three acceptability judgment experiments testing topicalization out of three adjunct clause types: om 'if', når 'when' and fordi 'because' in Norwegian. Largely replicating Kush et al. (2019), we find evidence for the absence of strong island effects with topicalization from om-adjuncts in all three experiments. We find island effects for når- and fordi-adjuncts, but the size of the effects and the underlying judgment distributions that produce those effects differ greatly by island type. Our results suggest that the syntactic category 'adjunct' may not constitute a suitably fine-grained grouping to explain variation in island effects. [ABSTRACT FROM AUTHOR]