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The goal of this paper is to investigate OpenStreetMap as a research tool by analysing what pros and cons this platform offers to linguistics and to GIS disciplines. To reach this goal, the paper analyses how this platform represents places as geographical units and toponyms (i.e. place names) as linguistic units referring to places. The paper presents two previous studies that featured a novel procedure for toponym extraction and its application to OpenStreetMap toponym data. These two studies focused on distinct scales and densities of geographical distribution in multi-lingual contexts: city level (Macao); mixed regional and national level (Italy). The studies also included a comparison of these data with data originating from an authoritative geographic source (e.g. Italian street directories). The present paper extends the analysis and results from these studies by showing that via a single extraction algorithm, one can obtain all the relevant toponyms from overpass-turbo, a platform including OpenStreetMap’s textual information, and from other gazetteers. For each level of analysis, the paper shows that toponyms come in different combinations of multi-lingual formats: Chinese and Portuguese for Macao, Italian, local dialects (e.g. Genoese), and minority languages (e.g. German) for Italy. From these data, the paper offers an analysis of language-specific features, methodological challenges, and informational accuracy of each database. The paper proposes that OpenStreetMap may be as reliable as authoritative sources; however, one must apply cross-source comparison during data analysis, to confirm OpenStreetMap-based data. The paper concludes by discussing the current role of OpenStreetMap as an information database in toponym extraction. The paper discusses the use of OSM in linguistics and GIS disciplines, and how these uses can offer theoretical insights informing research in these disciplines.

Clefts are understood as biclausal structures involving the movement of a clefted constituent from a lower clause, where it is generated, to a higher clause, where it is interpreted. Though both grammatical, subject and object clefts show signs of different acceptability in experimental settings. This degradation is ascribed to the fact that the object needs to cross an intervening subject, thus triggering intervention effects. In this paper, we show that intervention effects are also present in grammatical configurations, and give rise to lower-than-expected frequencies. Based on sets of features that play a role in the syntactic computation of locality, we compare the theoretically expected and the actually observed counts of features in a corpus of thirteen syntactically annotated treebanks for three languages (English, French, Italian). We find the quantitative effects predicted by the theory of intervention locality: object clefts are less frequent than expected in intervention configuration, while subject clefts are roughly as frequent as expected. We also find that the size of the effect is proportional to the number of features that give rise to the intervention effect. These results provide a three-fold contribution. First, they extend the empirical evidence in favour of the feature-based intervention theory of locality. Second, they provide theory-driven quantitative evidence, thus extending in a novel way the sources of evidence used to adjudicate theories. Finally, the paper provides a blueprint for future theory-driven quantitative investigations.

In this contribution, we use quantitative methods to account for trends of indefiniteness strategies (e.g. Italian Bevo del vino ‘I drink some wine’) in bilectal speakers of central Sicilian and Italian. These varieties differ in the available set (in terms of grammaticality and productivity) of indefiniteness strategies. The usage of these strategies may vary across speakers in this particular linguistic environment, showing tendencies towards one or the other variety. These trends can be easily quantified exploring relevant indices, such as the Index of Language Dominance (ILD; Birdsong et al. 2012). We perform a data analysis on the set of data collected, curated and annotated from two experimental situations by Di Caro (2023). In this respect, we also take into consideration the values annotated for the ILD, a quantitative measure to map grammars of bilinguals, although originally designed for linguistic scenarios where the two varieties are both official languages in the same country or in different countries. The strongest hypothesis we test is a clear correlation between the ILD and sets of syntactic strategies in Deliano. However, our results found no strong correlations between these two variables. We suggest that new parameters should be created to assess language dominance in bilectal speakers of Italian and other Italo-Romance varieties.

Clefts are understood as biciausai structures involving the movement of a ciefted constituent from a iower ciause, where it is generated, to a higher ciause, where it is interpreted. Though both grammaticai, subject and object ciefts show signs of different acceptabiiity in experimentai settings. This degradation is ascribed to the fact that the object needs to cross an intervening subject, thus triggering intervention effects. In this paper, we show that intervention effects are aiso present in grammaticai configurations, and give rise to iower-than-expected frequencies. Based on sets of features that piay a roie in the syntactic computation of iocaiity, we compare the theoreticaiiy expected and the actuaiiy observed counts of features in a corpus of thirteen syntacticaiiy annotated treebanks for three ianguages (Engiish, French, Itaiian). We find the quantitative effects predicted by the theory of intervention iocaiity: object ciefts are iess frequent than expected in intervention configuration, whiie subject ciefts are roughiy as frequent as expected. We aiso find that the size of the effect is proportionai to the number of features that give rise to the intervention effect. These resuits provide a three-foid contribution. First, they extend the empiricai evidence in favour of the feature-based intervention theory of iocaiity. Second, they provide theory-driven quantitative evidence, thus extending in a novei way the sources of evidence used to adjudicate theories. Finaiiy, the paper provides a biueprint for future theory-driven quantitative investigations.

The use of taboo words represents one of the most common and arguably universal linguistic behaviors, fulfilling a wide range of psychological and social functions. However, in the scientific literature, taboo language is poorly characterized, and how it is realized in different languages and populations remains largely unexplored. Here we provide a database of taboo words, collected from different linguistic communities (Study 1, N = 1046), along with their speaker-centered semantic characterization (Study 2, N = 455 for each of six rating dimensions), covering 13 languages and 17 countries from all five permanently inhabited continents. Our results show that, in all languages, taboo words are mainly characterized by extremely low valence and high arousal, and very low written frequency. However, a significant amount of cross-country variability in words’ tabooness and offensiveness proves the importance of community-specific sociocultural knowledge in the study of taboo language.

The goal of this paper is to offer an account of the discourse properties of urbanonynms in Italian (e.g. , ). The paper introduces urbanonyms as a sub-type of toponyms (place names) whose linguistic properties have received little attention so far. The paper proposes an experimental study that shows how urbanonyms can enter in anaphoric relations mediated via urbanonyms’ lexico-grammatical properties. Via these experimental results, it is shown that urbanonyms can act as antecedents of indexical pronouns (e.g. ‘here’), and complex noun phrases (e.g. ‘this street’). It is also shown that urbanonyms can involve co-referring patterns in sentences including ( ‘to be called’). These results are discussed against the theoretical proposals investigating toponyms and other proper names. It is suggested that the two main “rival” theories on names, the description theory and the causal reference theory, can only address the novel data if combined into a new theoretical synthesis.

In this paper, our goal is to investigate to what degree multilingual pretrained language models capture cross-linguistically valid abstract linguistic representations. We take the approach of developing curated synthetic data on a large scale, with specific properties, and using them to study sentence representations built using pretrained language models. We use a new multiple-choice task and datasets, Blackbird Language Matrices (BLMs), to focus on a specific grammatical structural phenomenon -- subject-verb agreement across a variety of sentence structures -- in several languages. Finding a solution to this task requires a system detecting complex linguistic patterns and paradigms in text representations. Using a two-level architecture that solves the problem in two steps -- detect syntactic objects and their properties in individual sentences, and find patterns across an input sequence of sentences -- we show that despite having been trained on multilingual texts in a consistent manner, multilingual pretrained language models have language-specific differences, and syntactic structure is not shared, even across closely related languages.

We investigate to what degree existing LLMs encode abstract linguistic information in Italian in a multi-task setting. We exploit curated synthetic data on a large scale -- several Blackbird Language Matrices (BLMs) problems in Italian -- and use them to study how sentence representations built using pre-trained language models encode specific syntactic and semantic information. We use a two-level architecture to model separately a compression of the sentence embeddings into a representation that contains relevant information for a task, and a BLM task. We then investigate whether we can obtain compressed sentence representations that encode syntactic and semantic information relevant to several BLM tasks. While we expected that the sentence structure -- in terms of sequence of phrases/chunks -- and chunk properties could be shared across tasks, performance and error analysis show that the clues for the different tasks are encoded in different manners in the sentence embeddings, suggesting that abstract linguistic notions such as constituents or thematic roles does not seem to be present in the pretrained sentence embeddings.

SARS-CoV-2 vaccination is effective in preventing severe Covid-19, but efficacy in reducing viral load and transmission wanes over time. In addition, the emergence of novel SARS-CoV-2 variants increases the threat of uncontrolled dissemination and additional antiviral therapies are urgently needed for effective containment. In previous in vitro studies Echinacea purpurea demonstrated strong antiviral activity against enveloped viruses, including SARS-CoV-2. In this study, we examined the potential of Echinacea purpurea in preventing and treating respiratory tract infections (RTIs) and in particular, SARS-CoV-2 infections. 120 healthy volunteers (m,f, 18—75 years) were randomly assigned to Echinacea prevention or control group without any intervention. After a run-in week, participants went through 3 prevention cycles of 2, 2 and 1 month with daily 2,400 mg Echinacea purpurea extract (Echinaforce ® , EF). The prevention cycles were interrupted by breaks of 1 week. Acute respiratory symptoms were treated with 4,000 mg EF for up to 10 days, and their severity assessed via a diary. Naso/oropharyngeal swabs and venous blood samples were routinely collected every month and during acute illnesses for detection and identification of respiratory viruses, including SARS-CoV-2 via RT-qPCR and serology. Summarized over all phases of prevention, 21 and 29 samples tested positive for any virus in the EF and control group, of which 5 and 14 samples tested SARS-CoV-2 positive (RR = 0.37, Chi-square test, p = 0.03). Overall, 10 and 14 symptomatic episodes occurred, of which 5 and 8 were Covid-19 (RR = 0.70, Chi-square test, p > 0.05). EF treatment when applied during acute episodes significantly reduced the overall virus load by at least 2.12 log 10 or approx. 99% ( t -test, p < 0.05), the time to virus clearance by 8.0 days for all viruses (Wilcoxon test, p = 0.02) and by 4.8 days for SARS-CoV-2 ( p > 0.05) in comparison to control. Finally, EF treatment significantly reduced fever days (1 day vs 11 days, Chi-square test, p = 0.003) but not the overall symptom severity. There were fewer Covid-19 related hospitalizations in the EF treatment group ( N = 0 vs N = 2). EF exhibited antiviral effects and reduced the risk of viral RTIs, including SARS-CoV-2. By substantially reducing virus loads in infected subjects, EF offers a supportive addition to existing mandated treatments like vaccinations. Future confirmatory studies are warranted.

Respiratory tract infections (RTIs) are the leading cause of antibiotic prescriptions, primarily due to the risk for secondary bacterial infections. In this study, we examined whether Echinacea could reduce the need for antibiotics by preventing RTIs and their complications, and subsequently investigated its safety profile. A comprehensive search of EMBASE, PubMed, Google Scholar, Cochrane DARE and clinicaltrials.gov identified 30 clinical trials (39 comparisons) studying Echinacea for the prevention or treatment of RTIs in 5652 subjects. Echinacea significantly reduced the monthly RTI occurrence, risk ratio (RR) 0.68 (95% CI 0.61–0.77) and number of patients with ≥1 RTI, RR = 0.75 [95% CI 0.69–0.81] corresponding to an odds ratio 0.53 [95% CI 0.42–0.67]. Echinacea reduced the risk of recurrent infections (RR = 0.60; 95% CI 0.46–0.80), RTI complications (RR = 0.44; 95% CI 0.36–0.54) and the need for antibiotic therapy (RR = 0.60; 95% CI 0.39–0.93), with total antibiotic therapy days reduced by 70% (IRR = 0.29; 95% CI 0.11–0.74). Alcoholic extracts from freshly harvested Echinacea purpurea were the strongest, with an 80% reduction of antibiotic treatment days, IRR 0.21 [95% CI 0.15–0.28]. An equal number of adverse events occurred with Echinacea and control treatment. Echinacea can safely prevent RTIs and associated complications, thereby decreasing the demand for antibiotics. Relevant differences exist between Echinacea preparations.