Abstract This paper revisits Pietroski’s challenge to truth-conditional semantics, focusing on his critique of Davidsonian event semantics in the case of mutual chases , which provide an intriguing exemplification of the complex interaction between logical forms and ambiguous contexts of utterance. Pietroski argues that truth-conditional analyses either collapse into contradiction or demand dubious metaphysical commitments, pushing us instead toward a purely procedural, concept-assembly view of meaning. Building on Quine’s “double-vision” puzzle, we defend truth-conditional semantics by introducing the notion of event guises : role-indexed properties of a single complex event. We argue that guises are supported not by subevents or perspectival constructs, but by minimal subsituations in Kratzer’s sense, i.e. informational parts of the situation that supports the event. This analysis dissolves apparent contradictions, preserves a lean ontology of events, and accommodates adverbial modification without metaphysical extravagance. The upshot is a hybrid event–situation semantics that shows why logical forms remain robustly truth-conditional, contra Pietroski’s skepticism.

Abstract In this paper, I discuss expressions such as ‘Dad’, ‘Mum’, ‘Grandpa’, etc., which are called ‘quasi-proper names’. These expressions can be used both to refer to a thing or person in an assertion in which a predicate is assigned to the referent expressed by the quasi-proper-name and to call somebody in particular (John!). In so far as they are indexical expressions, they are even more directly referential than proper names and guarantee discourse continuity to a greater extent than proper names (even if this appears to some to be controversial). To understand the working of quasi-proper names, I introduce a semantic rule that transforms nouns or definite descriptions into proper names and quasi-proper names, making the conceptual elements present in those expressions inactive and introducing a direct route from the proper name to the referent. Such a rule is synchronic, although it has diachronic consequences. Quasi-proper names can stimulate a debate about the function and role of proper names across cultures. I consider a number of expressions similar to quasi-proper names and I add the class of quasi-quasi-proper names (cases in which a term similar to a quasi-proper name can be used in vocatives but not in a subject-predicate structure, or, vice-versa, it can be used in a subject-predicate structure but not for vocatives).

Abstract Recent advancements in artificial intelligence technology have given impetus to extensive research across a number of disciplines, including semantics and pragmatics, which focus on human-machine linguistic interactions, dialogues in particular, that generate a feeling of almost natural conversation going on. The interest in such interactions has called to rethinking of pragmatic frameworks through which language use between human interlocutors is conceptualized. On the other hand, such research has affirmed that some pragmatic models, normally developed to pertain to human-human conversation, prove applicable and suitable to human-machine interaction, as is the sociocognitive approach (SCA). The concept that stands out in this respect is one of asymmetry in incrementing common ground between speakers that come from different languages. However, the subject of research presented in this paper are the fictional dialogues/conversations between characters in the novel by Kazuo Ishiguro, Klara and the Sun, that was first published four years ago. Following the trail of the question of credibility of fictional characters’ voices that has been illuminated in works on literary pragmatics and drawing on the concept of ‘in-betweenness’ (taken to be crucial for constructing culture by sociologists of culture) I examine those dialogues that Klara, a humanoid artificial friend (AF) enters within at least three different types of communities (K) - the community of other AFs and the communities she forms with humans – children and adults. Taking into account factors such as conceptual and background knowledge, egocentrism and salience, I observe the emergence of common ground between the fictional conversationalists, whom I take to be ‘intercultural speakers.’ The emergent common ground, however, consistently proves, in the majority of such conversations, deficient, cropped and unattainable. I argue, finally, that this failure to increment common ground gives credibility to Klara’s voice, making her a permanent ‘inbetweener.’

Abstract The study explores the effectiveness of ChatGPT in fostering intercultural pragmatic competence, focusing on Japanese learners of English. Using Kecskes’ sociocognitive framework, the research examines ChatGPT’s role in conversations involving meaning negotiation and repair mechanisms. The study analyzed over 10,000 responses generated by ChatGPT during interactions with 45 students from different nationalities, ranging from upper-beginner to upper-intermediate proficiency levels, in simulated social situations. A comprehensive examination of AI and participant responses and feedback yields a sophisticated understanding of the AI strengths and flaws, along with intercultural communication repair strategies for meaning negotiation. Specifically, findings reveal that while ChatGPT effectively models certain cooperative aspects of communication, it struggles with maintaining relevance and lacks human-like repair strategies. Students often initiate self-repair instead of other-repair, indicating limited interactive feedback from ChatGPT. Furthermore, excessive information. On the positive side, ChatGPT encourages confidence in students through predictions and co-constructed phrases, although its performance is repetitive and lacks deep contextual understanding. The study recommends cautious use of ChatGPT in pragmatic learning and highlights the need for more advanced frameworks to enhance AI’s role in intercultural communication education.

Abstract Conversational AI is advancing rapidly, enabling significant improvements in chatbots’ conversational abilities. Currently, available conversational chatbots (e.g., Snapchat’s MyAI) appear to generate fairly realistic, often human-like output. As collaboration between humans and machines becomes more common, and AI systems are increasingly viewed as more than just tools, understanding human communication in such contexts is crucial. Despite the vast array of applications and the increasing number of human-bot interactions, research on how humans interact with conversational chatbots is scarce. One possible reason for this gap is that studying human-computer communication may require adaptations of existing pragmatic frameworks, due to the unique characteristics of these interactions. A key feature of such conversations is their asymmetrical nature. In this paper, we present evidence that the sociocognitive approach (SCA), which takes into account the asymmetry between interlocutors as regards their possible common grounds, has explanatory potential to describe human-AI-powered chatbot interactions. We collected data from thirty-two L1 Hungarian participants interacting with a conversational chatbot on three consecutive days. The turn-by-turn analysis of the 96 conversations provides insights not only into the nature of common ground humans presuppose with a conversational agent, but also into the processes of building emergent common ground over time. Furthermore, we present linguistic evidence that both egocentrism and cooperation play a role in human-chatbot interaction. While the former is manifested in approaching the chatbot as if it were human, the latter appears to play a role in changing strategies that serve common ground seeking and building.

Abstract It has been argued that the distribution of pronominal forms in pro-drop languages is shaped by a complex interplay of syntactic, semantic, and pragmatic factors. Null pronouns are typically interpreted as co-referring with the most prominent antecedent, whereas overt pronouns often signal a topic shift, co-referring with less prominent antecedents. Although many frameworks have been proposed to explain the division of labor between null and overt pronouns, empirical studies on anaphora resolution in causative sentences remain scarce. In this study, 41 Italian native speakers completed a referential selection task involving subject-biased or object-biased complex causative sentences with either a null or an overt pronoun. Results revealed a strong reliance on discourse-level factors, with participants consistently selecting the pragmatically appropriate antecedent regardless of pronoun type. However, eye-tracking data showed higher processing costs in accommodating violations of the typical pronoun-antecedent combinations. This was especially true in subject-biased sentences with an overt pronoun but was also observed in object-biased sentences with a null pronoun. These findings suggest that, while pragmatic factors largely drive anaphoric resolution in causative sentences, pronoun type leads to different processing costs in contexts where the pragmatic antecedent does not align with the expected pronoun type.