Band 18, Heft 3

Based on corpus data and adopting a behavioral profile approach, this study examines the time orientation of Chinese words qian “front” and hou “back.” The corpus analysis yields the following findings. First, the primary temporal meaning of qian and hou is indicating time sequence, with qian meaning “earlier” and hou meaning “later.” Second, Chinese speakers tend to conceptualize the future as being ahead of them and the past behind them. Both qian and hou are found to refer to the past and the future. Their contradictory usage arises from the lack of a distinction between Ego-Reference-Point and Time-Reference-Point. Third, qian and hou are used mainly in five constructions as temporal words. Their constructional profiles reveal that their time orientation correlates with the constructions in which they occur. Based on the corpus results, I also discuss the motivations underlying their time orientation in various constructions and argue that their time orientation stems from an interplay of temporal metaphors, the constructions in which they occur, and context. These findings suggest that speakers’ metaphorical representations of time are shaped by a multitude of factors rather than single space-to-time mappings.

Usage-based approaches assume that children’s early utterances are item-based. This has been demonstrated in a number of studies using the traceback method. In this approach, a small amount of “target utterances” from a child language corpus is “traced back” to earlier utterances. Drawing on a case study of German, this paper provides a critical evaluation of the method from a usage-based perspective. In particular, we check how factors inherent to corpus data as well as methodological choices influence the results of traceback studies. To this end, we present four case studies in which we change thresholds and the composition of the main corpus, use a cross-corpus approach tracing one child’s utterances back to another child’s corpus, and reverse and randomize the target utterances. Overall, the results show that the method can provide interesting insights—particularly regarding different pathways of language acquisition—but they also show the limitations of the method.

This paper studies the implicit structures and the diffusion modes of semantic prosody on the dependency networks of some English words such as cause and their Chinese equivalents. It is found that the structure of semantic prosody is a bi-stratified network consisting of a few large clusters gathering in the center with most nodes of low dependency capability scattered around. With regard to the diffusion modes, results show that: (i) within one shortest path length, the core words directly attract the nodes with the same or similar semantic characteristics and exclude those with conflicting ones, creating the clearest and the most intense semantic diffusion; (ii) over one shortest path length, semantic diffusion is achieved through content words or function words, and the semantic diffusion modes created with function words as bridges are relatively vaguer and more complicated ones. This conclusion also results in the semantic prosodies of other English words and their Chinese equivalent words, revealing, to some extent, a common cognitive approach to understanding the internal structure and the diffusion modes of semantic prosody.

In structuralist linguistics, compounds are argued not to constitute morphological categories, due to the absence of systematic form-meaning correspondences. This study investigates subsets of compounds for which systematic form-meaning correspondences are present: adjective–noun compounds in Mandarin. We show that there are substantial differences in the productivity of these compounds. One set of productivity measures (the count of types, the count of hapax legomena, and the estimated count of unseen types) reflect compounds’ profitability. By contrast, the category-conditioned degree of productivity is found to correlate with the internal semantic transparency of the words belonging to a morphological category. Greater semantic transparency, gauged by distributional semantics, predicts greater category-conditioned productivity. This dovetails well with the hypothesis that semantic transparency is a prerequisite for a word formation process to be productive.

Indonesian has two prefixes, PE- and PEN- , that are similar in form and meaning, but are probably not allomorphs. In this study, we applied a distributional vector space model to clarify whether these prefixes have discriminable semantics. Comparisons of pairs of words within and across morphologically defined sets of words revealed that cosine similarities of pairs consisting of a word with PE- and a word with PEN- were reduced compared to pairs of only PE- words, or of only PEN- words. Furthermore, nouns with PE- were more similar to their base words than was the case for words with PEN- . The specialized use of PE- for words denoting agents, and the specialized use of PEN- for denoting instruments, was also visible in the semantic vector space. These differences in the semantics of PE- and PEN- thus provide further quantitative support for the independent status of PE- as opposed to PEN- .

This corpus-based study focuses on the progressive:non-progressive alternation from a novel perspective, i.e. the effect of syntactic priming. We annotated a dataset of 5,000 progressive and non-progressive occurrences in ten different varieties of English from the International Corpus of English for variables such as Aktionsart categories and elements related to priming and subjected the data to a generalized linear mixed methods tree analysis. The results indicate that the progressive is most likely to occur in situations that are durative in nature and when they are preceded by another progressive; overall, we find some evidence of probabilistic indigenization with regard to the use of progressives in different varieties. However, while syntactic priming seems to play a role overall in the choice of the progressive over the non-progressive, we do not find evidence supporting the idea that priming may explain the use of non-standard stative progressives.

This paper reports on the state-of-the-art in application of multidimensional scaling (MDS) techniques to create semantic maps in linguistic research. MDS refers to a statistical technique that represents objects (lexical items, linguistic contexts, languages, etc.) as points in a space so that close similarity between the objects corresponds to close distances between the corresponding points in the representation. We focus on the use of MDS in combination with parallel corpus data as used in research on cross-linguistic variation. We first introduce the mathematical foundations of MDS and then give an exhaustive overview of past research that employs MDS techniques in combination with parallel corpus data. We propose a set of terminology to succinctly describe the key parameters of a particular MDS application. We then show that this computational methodology is theory-neutral, i.e. it can be employed to answer research questions in a variety of linguistic theoretical frameworks. Finally, we show how this leads to two lines of future developments for MDS research in linguistics.