We introduce an extensive dataset for multilingual probing of morphological information in language models (247 tasks across 42 languages from 10 families), each consisting of a sentence with a target word and a morphological tag as the desired label, derived from the Universal Dependencies treebanks. We find that pre-trained Transformer models (mBERT and XLM-RoBERTa) learn features that attain strong performance across these tasks. We then apply two methods to locate, for each probing task, where the disambiguating information resides in the input. The first is a new perturbation method that “masks” various parts of context; the second is the classical method of Shapley values. The most intriguing finding that emerges is a strong tendency for the preceding context to hold more information relevant to the prediction than the following context.

Argumentation problems are concerned with determining the acceptability of a set of arguments from their relational structure. When the available information is uncertain, probabilistic argumentation frameworks provide modeling tools to account for it. The first contribution of this paper is a novel interpretation of probabilistic argumentation frameworks as probabilistic logic programs. Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. We show that the programs representing probabilistic argumentation frameworks do not satisfy a common assumption in probabilistic logic programming (PLP) semantics, which is, that probabilistic facts fully capture the uncertainty in the domain under investigation. The second contribution of this paper is then a novel PLP semantics for programs where a choice of probabilistic facts does not uniquely determine the truth assignment of the logical atoms. The third contribution of this paper is the implementation of a PLP system supporting this semantics: smProbLog. smProbLog is a novel PLP framework based on the PLP language ProbLog. smProbLog supports many inference and learning tasks typical of PLP, which, together with our first contribution, provide novel reasoning tools for probabilistic argumentation. We evaluate our approach with experiments analyzing the computational cost of the proposed algorithms and their application to a dataset of argumentation problems.

The article explores the prosodic and kinesic aspects of three different ish constructions using corpus data from the multimodal NewsScape Library of International Television News. The results reveal that bound -ish with ‘approximate’ meaning is longer in duration, higher in pitch, and shows more pitch variability than bound -ish with ‘properties’ meaning. Free Ish is also longer in duration and shows more pitch variability but is also prosodically set apart from its linguistic environment. Furthermore, the different ish constructions prove to be associated with different sets of kinesic features, although none of these reaches a significant level in the statistical model. It will be argued that the prosodic aspects mirror the constructional status of ish, whereas the kinesic aspects may be used to support their different functions.

This article discusses the development of an automated plot extraction system for narrative texts. Acknowledging the distinction between plot, as an object of study with its own rich history and literature, and features of a text that may be automatically extractable, we begin by characterizing a text’s scatter plot of entities. This visualization of a text reveals entity density patterns characterizing the particular telling of the story under investigation and leads to effective scene partitioning. We then introduce the concept of narrative flow, a graph representation of the narrative ordering of scenes (the syuzhet) that includes how entities move through scenes from the text, and investigate the degree to which narrative flow can be automatically extracted given a glossary of plot-important objects, actors, and locations. Our subsequent analysis then explores the correlation between subjective notions of plot and the information extracted through these visualizations. In particular, we discuss narrative structures commonly found within the graphs and make comparisons with ground truth narrative flow graphs, showing mixed results highlighting the difficulty of plot extraction. However, the visual artifacts and common structural relationships seen in the graphs provide insight into narrative and its underlying plot.

Williams syndrome (WS) is a rare genetic disorder, characterised at the cognitive level by a phenotypic pattern of relative weaknesses (e.g., visuospatial skills) and strengths (e.g., some linguistic and nonverbal reasoning skills). In this study, we performed a systematic search and meta-analysis on lexical-semantic processing in WS, an area of knowledge in which contradictory results have been obtained. We found 42 studies matching our criteria, and, in total, 78 effect sizes were included in the meta-analysis. Results showed that individuals with WS have worse lexical-semantic skills than individuals with typical development, whether matched by chronological or mental age. However, people with WS have better lexical-semantic skills than people diagnosed with other cognitive disabilities. Finally, vocabulary skills seem to be relatively spared in WS, although they present some difficulties in semantic processing/integration, semantic memory organisation and verbal working memory skills. Taken together, these results support a neuroconstructivist approach, according to which the cognitive mechanisms involved in lexical-semantic processing may be modulated, even when performance in some tasks (i.e., vocabulary tasks) might be optimal.

Convincing narratives are not confabulations. Presumably they “feel right” to decision-making agents because the probabilities they assign intuitively (i.e., implicitly) to potential outcomes are plausible. Can we render explicit the calculations that would be performed by a decision-making agent to evaluate the plausibility of competing narratives? And if we can, what, exactly, makes a narrative “feel right” to an agent?

In his ‘script theory,' Tomkins first proposed that people unconsciously organize their life experiences in terms of narrative structures he termed “scripts.” I use a clinical vignette to illustrate how the psychotherapeutic process of “making the unconscious conscious” involves becoming aware of the maladaptive scripts that people unwittingly live by, and developing them into the “conviction narratives” proposed by the authors.

We study site and bond percolation in simple directed random graphs with a given degree distribution. We derive the percolation threshold for the giant strongly connected component and the fraction of vertices in this component as a function of the percolation probability. The results are obtained for degree sequences in which the maximum degree may depend on the total number of nodes n, being asymptotically bounded by $n^{\frac{1}{9}}$.

Mentored online intercultural interaction offers foreign language learners the opportunity to develop different competences, including intercultural, linguistic, and digital competence (O’Dowd, 2021). Such virtual exchange (VE) projects typically involve computer-mediated communication via, for example, Zoom. However, the use of high-immersion virtual reality (VR) for synchronous online collaboration in VE projects has received little attention. This study investigated the effect of VR on students’ levels of presence and engagement, on students’ communication and on students’ views on using VR for intercultural encounters compared to traditional videoconferencing tools. Twenty-seven university students from the Netherlands and Germany utilised VR to carry out intercultural learning tasks using English as a lingua franca during a four-week implementation period. Participants responded to pre- and post-intervention questionnaires, completed reflection journals, audio- or video-recorded their VR meetings and participated in interviews. Results showed that the levels of presence and engagement and preferences of social VR compared to videoconferencing for intercultural encounters depended on students individually. A VR immersion experience and comfortability scale was created based on the data which showed mixed experiences. VR influenced participants’ interactions, topics of conversation and communication strategies when they explored their spaces together. The results showed that students’ attitudes towards VR and their subjective experience of VR seem to play an important role in the VE-VR setting. VR provided a safe space for many participants. Positive attitudes towards communicating in the VR environment are highly correlated with positive attitudes towards meeting students from other countries in VR. Implications for language education are provided.

The aim of this study was to better understand the relation of schizotypy traits with sensory gating ability in a sample of community-dwelling individuals with high and low schizotypy traits. Sensory gating was assessed through the paired click paradigm and mid-latency evoked responses (i.e., P50, N100, P200), while schizotypy traits were assessed through the SPQ-BR which was used to classify participants into “high” and “low” schizotypy groups. Based on prior work, we hypothesized that those with the highest schizotypy scores would have reduced sensory gating ability. While this study does not show differences between relatively low and high schizotypy groups on sensory gating ability, it does suggest that our participants may have been experiencing deficits in attention allocation, a downstream cognitive processing measure. Scores on the SPQ-BR suggest that our sample was not close to the high end of the schizotypy traits which may help explain why no differences were found. This research shows the importance of including all levels of schizotypy ratings in clinical research as we can gain a clearer view of the impact of schizotypy on the brain and cognitive functioning in those with “high” levels of schizotypy. Additionally, this work highlights the importance of including measures of important factors such as impulsivity and sensation-seeking to better understand what aspects of schizotypy may be driving these sensory gating alterations reported in the literature.

Link traversal–based query processing (ltqp), in which a sparql query is evaluated over a web of documents rather than a single dataset, is often seen as a theoretically interesting yet impractical technique. However, in a time where the hypercentralization of data has increasingly come under scrutiny, a decentralized Web of Data with a simple document-based interface is appealing, as it enables data publishers to control their data and access rights. While (ltqp allows evaluating complex queries over such webs, it suffers from performance issues (due to the high number of documents containing data) as well as information quality concerns (due to the many sources providing such documents). In existing ltqp approaches, the burden of finding sources to query is entirely in the hands of the data consumer. In this paper, we argue that to solve these issues, data publishers should also be able to suggest sources of interest and guide the data consumer toward relevant and trustworthy data. We introduce a theoretical framework that enables such guided link traversal and study its properties. We illustrate with a theoretic example that this can improve query results and reduce the number of network requests. We evaluate our proposal experimentally on a virtual linked web with specifications and indeed observe that not just the data quality but also the efficiency of querying improves.

We obtain, for the first time, a modular many-valued semantics for combined logics, which is built directly from many-valued semantics for the logics being combined, by means of suitable universal operations over partial non-deterministic logical matrices. Our constructions preserve finite-valuedness in the context of multiple-conclusion logics, whereas, unsurprisingly, it may be lost in the context of single-conclusion logics. Besides illustrating our constructions over a wide range of examples, we also develop concrete applications of our semantic characterizations, namely regarding the semantics of strengthening a given many-valued logic with additional axioms, the study of conditions under which a given logic may be seen as a combination of simpler syntactically defined fragments whose calculi can be obtained independently and put together to form a calculus for the whole logic, and also general conditions for decidability to be preserved by the combination mechanism.

We initiate the study of computable presentations of real and complex C*-algebras under the program of effective metric structure theory. With the group situation as a model, we develop corresponding notions of recursive presentations and word problems for C*-algebras, and show some analogous results hold in this setting. Famously, every finitely generated group with a computable presentation is computably categorical, but we provide a counterexample in the case of C*-algebras. On the other hand, we show every finite-dimensional C*-algebra is computably categorical.

The global and uneven spread of COVID-19, mirrored at the local scale, reveals stark differences along racial and ethnic lines. We respond to the pressing need to understand these divergent outcomes via neighborhood level analysis of mobility and case count information. Using data from Chicago over 2020, we leverage a metapopulation Susceptible-Exposed-Infectious-Removed model to reconstruct and simulate the spread of SARS-CoV-2 at the ZIP Code level. We demonstrate that exposures are mostly contained within one’s own ZIP Code and demographic group. Building on this observation, we illustrate that we can understand epidemic progression using a composite metric combining the volume of mobility and the risk that each trip represents, while separately these factors fail to explain the observed heterogeneity in neighborhood level outcomes. Having established this result, we next uncover how group level differences in these factors give rise to disparities in case rates along racial and ethnic lines. Following this, we ask what-if questions to quantify how segregation impacts COVID-19 case rates via altering mobility patterns. We find that segregation in the mobility network has contributed to inequality in case rates across demographic groups.

It is controversial which idioms can occur with which syntactic structures. For example, can Mary kicked the bucket (figurative meaning: ‘Mary died’) be passivized to The bucket was kicked by Mary? We present a series of experiments in which we test which structures are compatible with which idioms in German (for which there are few experimental data so far) and English, using acceptability judgments. For some of the tested structures – including German left dislocation, scrambling, and prefield fronting – it is particularly contested to what extent they are restricted by semantic factors and, as a consequence, to what extent they are compatible with idioms. In our data, these structures consistently showed similar limitations: they were fully compatible with one subset of our test idioms (those categorized as semantically compositional) and degraded with another (those categorized as non-compositional). Our findings only partly align with previously proposed hierarchies of structures with respect to their compatibility with idioms.

The concept of ‘snowclones’ has gained interest in recent research on linguistic creativity and in studies of extravagance and expressiveness in language. However, no clear criteria for identifying snowclones have yet been established, and detailed corpus-based investigations of the phenomenon are still lacking. This paper addresses this research gap in a twofold way. On the one hand, we develop an operational definition of snowclones, arguing that three criteria are decisive: (i) the existence of a lexically fixed source construction; (ii) partial productivity; (iii) ‘extravagant’ formal and/or functional characteristics. On the other hand, we offer an empirical investigation of two patterns that have often been mentioned as examples of snowclones in the previous literature, namely [the mother of all X] and [X BE the new Y]. We use collostructional analysis and distributional semantics to explore the partial productivity of both patterns’ slot fillers. In sum, we argue that the concept of snowclones, if properly defined, can contribute substantially to our understanding of creative language use, especially regarding the question of how social, cultural, and interpersonal factors influence the choice of more or less salient linguistic constructions.

This meta-analytic study explores the overall effectiveness of automatic speech recognition (ASR) on ESL/EFL student pronunciation performance. Data with 15 studies representing 38 effect sizes found from 2008 to 2021 were meta-analyzed. The findings of the meta-analysis indicated that ASR has a medium overall effect size (g = 0.69). Results from moderator analyses suggest that (1) ASR with explicit corrective feedback is largely effective, while ASR with indirect feedback (e.g. ASR dictation) is moderately effective; (2) ASR has a large effect on segmental pronunciation but a small effect on suprasegmental pronunciation; (3) medium to long treatment duration of ASR results in higher learning outcomes, but short duration offers no differential effect compared to a non-ASR condition; (4) practicing pronunciation with peers in an ASR condition produces a large effect, but the effect is small when practicing alone; (5) ASR is largely effective for adult (i.e. 18 years old and above) and intermediate English learners. Overall, ASR is a beneficial application and is recommended for assisting L2 student pronunciation development.

In this paper, we establish some stochastic comparison results for largest claim amounts of two sets of independent and also for interdependent portfolios under the setup of the proportional odds model. We also establish stochastic comparison results for aggregate claim amounts of two sets of independent portfolios. Further, stochastic comparisons for largest claim amounts from two sets of independent multiple-outlier claims have also been studied. The results we obtained apply to the whole family of extended distributions, also known as the Marshall–Olkin family of distributions. We have given many numerical examples to illustrate the results obtained.