Volume 18, Issue 2

In this study, we aim to demonstrate the effectiveness of network science in exploring the emergence of constructional semantics from the connectedness and relationships between linguistic units. With Mandarin locative constructions (MLCs) as a case study, we extracted constructional tokens from a representative corpus, including their respective space particles (SPs) and the head nouns of the landmarks (LMs), which constitute the nodes of the network. We computed edges based on the lexical similarities of word embeddings learned from large text corpora and the SP-LM contingency from collostructional analysis. We address three issues: (1) For each LM, how prototypical is it of the meaning of the SP? (2) For each SP, how semantically cohesive are its LM exemplars? (3) What are the emerging semantic fields from the constructional network of MLCs? We address these questions by examining the quantitative properties of the network at three levels: microscopic (i.e., node centrality and local clustering coefficient), mesoscopic (i.e., community) and macroscopic properties (i.e., small-worldness and scale-free). Our network analyses bring to the foreground the importance of repeated language experiences in the shaping and entrenchment of linguistic knowledge.

The investigation of linguistic phenomena in corpora of spontaneous speech is sometimes hindered by corpus size or by the complexity of the factors influencing their occurrence. Language Production Experiments (LPEs) can specifically elicit such phenomena and can therefore be used to build corpora that allow for their investigation. Yet experiments are a wide category that covers very different tasks, and there is little empirical research that compares speakers’ response behavior to different task types. In this paper, we compare the responses of a group of 22 speakers to a translation task and a completion task, both of which target the syntactic phenomena complementizer agreement (CA). The results indicate that both experimental methods offer legitimate ways to investigate the phenomenon with specific advantages and disadvantages. However, a comparison of results from both tasks allows for insights that a single task could not have provided.

This behavioural profiling (BP) study examines the use of the near-synonyms rang (讓), shi (使) and ling (令), three ways to express cause-effect relationships in Chinese. Instead of using an out-of-the-box BP design, we present a modified approach to profiling that includes a range of frame semantic features that aim to capture variation of slot fillers of this construction. The study investigates the intricate semantic variation of rang , shi and ling through a comprehensive analysis of 38 contextual features (ID tags) that characterize the collocational, lexical semantic and frame semantic environment of the near-synonyms. Our dataset consists of around 100.000 data points based on the annotation of 1002 sentences of Mandarin Chinese of three varieties. The BPs of each near-synonym are compared using multidimensional scaling and hierarchical cluster analysis. The results show that rang , shi and ling are each characterized by a combination of distinctive features and how different feature types contribute to setting the near-synonyms apart based on their usage patterns. Methodologically, this study illustrates how behavioural profiling can be modified to include frame semantic features in accordance with the method’s emphasis on producing empirically verifiable results and how these features can aid a comparative analysis of near-synonyms.

This study investigates the developmental trajectory of L2 English progressive construction with a focus on frequency, verb-construction contingency and semantic prototypicality. Comparisons were made on the use of the progressive construction in argumentative essays written by Chinese learners at three different proficiency levels and English native speakers. Data of frequency and verb type distribution indicate that L2 learners’ progressive repertoire showed an increase in productivity and variability and a spread from a fixed type to a wider range of verbs. Contingency data demonstrate that, when associating verbs with the progressive, learners’ preference shifted from prototypical progressive verbs which denote specific and dynamic meanings to more marginal members represented by generic verbs. In addition, semantic prototypicality overweighs generality in driving the development of the progressive, which presents an interesting contrast with findings in the verb-argument construction learning literature where semantically general verbs were first predominantly used in the construction.

This paper innovatively charts the analogical influence of the modal auxiliaries on the regulation of periphrastic do in Early Modern English by means of Convolutional Neural Networks (CNNs), a flavour of connectionist models known for their applications in computer vision. CNNs can be harnessed to model the choice between competitors in a linguistic alternation by extracting not only the contexts a construction occurs in, but also the contexts it could have occurred in, but did not. Bearing on the idea that two forms are perceived as similar if they occur in similar contexts, the models provide us with pointers towards potential loci of analogical attraction that would be hard to retrieve otherwise. Our analysis reveals clear functional overlap between do and all modals, indicating not only that analogical pressure was highly likely, but even that affirmative declarative do functioned as a modal auxiliary itself throughout the late 16th century.

English exerts great influence on other languages at the lexical level, as seen from extensive borrowing of terminology and everyday words into many languages (i.e. Anglicisms such as swap, blog, etc.). Although much less studied, it is also clear that the “phrasicon” (Granger, Sylviane. 2009. Comment on: learner corpora: A window onto the L2 phrasicon. In Andy Barfield & Henrik Gyllstad (eds.), Researching collocations in another language. multiple interpretations , 60–65. Houndmills: Palgrave Macmillan) of a language can similarly be affected by such external influence. This paper investigates “the largely unexplored area of phraseological borrowing” (Fielder, Sabine (2017) Phraseological borrowing from English into German: Cultural andpragmatic implications.  Journal of Pragmatics  113: 89–102, 90) by introducing the diachronic-contrastive corpus method and exemplifying it with reference to a set of expressions that have been considered the products of language contact between English and Norwegian. I argue that the proposed corpus method can be used efficiently for investigating phraseology across time, for shedding light on the question of whether cross-linguistically parallel structures are the result of borrowing or parallel developments, and – importantly – as a vehicle for rejecting preconceived ideas about a form’s alleged origin in English.

Traditionally, automated methods for loanword detection have not received an abundance of attention within the field of language contact. However, as research on loanwords has begun utilizing corpora with word counts in the millions, these generous quantities of data pose challenges for traditional methods of linguistic annotation. This paper presents a method for automatically detecting anglicisms within Spanish text and presents a case study, applying this method to explore the social stratification of anglicisms in Argentine media. The findings of the case study suggest that anglicisms may function as prestige markers in Argentina, which may be a logical consequence of the mode of contact: those of upper socio-economic status have greater access to outlets where loanwords seem to emerge, such as the media, Internet, and second language education.

The correspondence between the communicative intention of a speaker in terms of Information Structure and the way this speaker reflects communicative aspects by means of prosody have been a fruitful field of study in Linguistics. However, text-to-speech applications still lack the variability and richness found in human speech in terms of how humans display their communication skills. Some attempts were made in the past to model one aspect of Information Structure, namely thematicity for its application to intonation generation in text-to-speech technologies. Yet, these applications suffer from two limitations: (i) they draw upon a small number of made-up simple question-answer pairs rather than on real (spoken or written) corpus material; and (ii) they do not explore whether any other interpretation would better suit a wider range of textual genres beyond dialogs. In this paper, two different interpretations of thematicity in the field of speech technologies are examined: the state-of-art binary (and flat) theme-rheme, and the hierarchical thematicity defined by Igor Mel’čuk within the Meaning-Text Theory. The outcome of the experiments on a corpus of native speakers of US English suggests that the latter interpretation of thematicity has a versatile implementation potential for text-to-speech applications of the Information Structure – prosody interface.