When language users choose between alternative schematic constructions, as for example in the English dative alternation, they are influenced not only by contextual or processing-related factors that apply generally but also by individual lexemes that fill the open slots of constructions. The methodology for modeling such lexical biases is still under development. To motivate methodological decisions, we need a theory of how lexical biases arise in the first place. Drawing on usage-based theory, this paper argues that lexical biases emerge from exemplars of concrete, lexically specific instances, from which generalizations are formed. The resulting hierarchical structure enables speakers to learn lexical biases efficiently by drawing on expectations derived from these generalizations. This assumption parallels the logic of multilevel (hierarchical) modeling, in which the effects of random groups are estimated jointly under a shared distribution, while also being separately estimated for each group. In order to support this claim, the present paper revisits the English dative alternation. We employ a Bayesian multilevel regression model in order to demonstrate its viability for capturing the lexical specificities of alternating constructions. Our case study serves to illustrate technical aspects of the method, such as specifying the group-level effects structure and setting priors.
The present study employs the Behavioral Profile approach to better understand the distribution and use of weak epistemic adverbs in Colombian Spanish. Tokens of six synonymous adverbs (a lo mejor, de pronto, posiblemente, quiz & aacute;, quiz & aacute;s, tal vez) were extracted from Corpus del Espa & ntilde;ol (Web/Dialect) and coded for seven syntactic and semantic variables. The results of multiple hierarchical configural frequency analyses found that, while the adverbs share a common core profile, there are distributional differences related to clause position, grammatical mood, and temporal reference. The synchronic results are argued to align with previous diachronic research on epistemic adverbs. Namely, it was found that adverbs that entered the language more recently as epistemic (a lo mejor, de pronto) had less syntactic freedom, mainly appeared with verbs in the indicative, and showed a slight preference for future-oriented contexts - features seen in the earlier developmental stages of epistemic adverbs.
Investigations of adjective order in English have primarily focused on the attributive use type. However, adjectives can also occur in predicative contexts. This study extends the analysis of juxtaposed attributive adjective sequences to coordinated attributive and (coordinated) predicative uses and examines whether the same ordering constraints are at work in the three conditions. A distinction is made between semantic and activation-based variables. Juxtaposed attributive adjective dyads are found to be sensitive to semantic but less sensitive to activation-based variables whereas the opposite is true of coordinated attributive and predicative adjective pairs. Thus, coordinated attributive and predicative adjectives behave alike while juxtaposed attributive adjectives stand apart. Semantic and activation-based variables are argued to stand in a complementary relationship. The importance of semantic constraints in juxtaposed attribution follows from the desire to facilitate the recognition of the upcoming noun. By contrast, the importance of activation-based variables in coordinated attribution and predication results from the limited role of semantic constraints in these two conditions.
Identifying lexical semantic differences across closely related language varieties remains methodologically challenging, as traditional approaches often rely on intuition, manual inspection, or researcher-constructed word lists with limited coverage. This study proposes a computational framework that uses word embedding models to automatically detect lexical semantic variation in large comparable corpora. Using Hong Kong written Chinese as the primary case and Mainland China written Chinese as a point of comparison, we show that the approach not only recovers well-documented differences reported in previous research, but also identifies less salient cases that are easily missed by manual methods. The results demonstrate that the proposed framework provides broader empirical coverage, reduces reliance on subjective discovery, and scales effectively to large datasets. More broadly, the study highlights the value of embedding-based methods for investigating lexical semantic variation across language varieties.
This study investigates the constructional organization of modal interrogatives by examining how modal meaning shapes response behavior. Previous research on question-response systems has largely focused on canonical polar questions, treating response particles such as yes and no as markers of propositional polarity. However, modal interrogatives introduce additional interpretive dimensions in which responses may perform discourse actions such as authorization, refusal, or epistemic endorsement. To examine whether modal interrogatives exhibit construction-specific response patterns, this study analyzes may and might interrogatives using corpus-based collostructional analysis and large language model surprisal measures. Collostructional analysis identifies distributional associations between interrogative constructions and lexical items, while LLM-based surprisal provides a probabilistic diagnostic of semantic compatibility in constructional contexts. The results reveal systematic constructional differentiation between the two constructions. The may interrogative strongly attracts first-person subjects, interaction-oriented verbs, and affirmative responses, signifying its prototypical permission-seeking use. In contrast, the might interrogative preferentially combines with non-first-person subjects, stative predicates, and evaluative responses associated with epistemic assessment. Surprisal values align with these distributional preferences, indicating that lexically compatible realizations are more strongly predicted in context. These findings suggest that modal interrogative-response pairings constitute discourse-level constructions characterized by both distributional entrenchment and probabilistic expectancy.
