It is an orthodoxy championed by Kripke that Frege’s theory of sense is an semantic theory. With Frege’s focus on abstract objects as examples, I point out that much can be learned from Kripke’s metaphysics and epistemology, but I disagree with him with my epistemological theory of sense. Abstract objects are the way they are necessarily, but concrete objects are often not; if sense is objective, is it then necessary? That Hesperus occupies a given position in the evening sky constitutes the sense of the proper name ‘Hesperus’, which, if one were to interact appropriately with others in a linguistic community using that name, one is to know, but Venus could have been knocked out of its course. If sense is modifiable, how is it still objective? Besides the exegetical contention that Frege’s theory of sense is epistemological, I will also develop a measure of objectivity along representation, or Vorstellung, which cuts across belief and knowledge. A representation reaching a given objectivity constitutes sense, and I explore whether objectivity is explained with justifiability thus. I propose a common ground conception of sense that is epistemological, which connects to the orthodoxy through linguistic conventionality.

Speaking about the differences in foreign language teaching methods, one usually relies on the difference in the organisation of linguistic material, the proportion of the native language, and the teacher-student roles. Neurophysiological correlates of oscillatory brain activity, however, are more objective indicators, since they directly reflect the organisation of brain activity during the process of foreign language learning depending on the chosen methodology. The aim was to establish correlations of neurophysiological parameters in the participants of the control and main groups, learning German using the communicative method, on the one hand, and that of the deep semantics theory by P. Y. Galperin, as well as the stage-by-stage formation theory of mental activity, on the other. The material was obtained in a 3-stage study, with 6 participants, 4 male and 12 female ones, aged 19–21. The following design was chosen for the study: 1. Conducting the first experiment for the main and control group with the variant evaluation while translating a phrase from Russian into German as ‘exactly correct’, ‘rather correct’, ‘exactly wrong’ or ‘rather wrong’. 2. A break accompanied by training in the methods chosen for each group. 3. Running a second experiment for both groups with the variant re-evaluation while translating a phrase from Russian into German using the same categories as before. Brain Products amplifier and PyCorder software were used for EEG recording, MATLAB with EEGLAB software tool was used for preprocessing and analysis, IBM SPSS package was used for statistical analysis of EEG data. The statistical data with the evaluation of translation options were further processed using Excel functionality. Students from both groups showed a significant difference at the behavioral level in terms of the average time of solving tasks and in the organisation of activity in the sagittal cortical areas, as well as at the level of academic results. The obtained results allow us to point out certain differences in the cognitive strategies of the participants of the control and main groups, namely: in the control group, the earlier strategy of cognitive processing of stimuli intensified in the process of learning German, while in the main group it changed to something qualitatively different, which gives us an opportunity to assume the presence of a qualitative transition of the participants of the main group during the repeated measurement from one cognitive strategy of solving the translation and categorisation task to another. Thus, for exam ple,synchronisation with an amplitude maximum in the beta range (16–31 Hz) in participants of the main group during repeated readings can be assessed as a neurophysiological correlate of ‘semantic synthesis’, in which a learner combines several semantic items into a total syntactically related construction.

Comparative component analysis based on semantic features has long been a common method in contrastive lexical-semantic studies. Comparative component analysis of the content of lexical units of two languages consists in separating the meanings of these units into semantic features and determining which of their semantic features coincide and which differ.

Abstract Lexical ambiguity, where a word has multiple related (polysemous) and/or unrelated (homographic) meanings, causes challenges in learning and teaching semi-technical medical vocabulary owing to its lack of consideration in current lexicographical resources, including wordlists and dictionaries. Academic wordlists fail to indicate polysemes and homographs, while conventional dictionaries number multiple meanings of a semi-technical medical word in a vertical format that is unlikely to showcase polysemous and homographic relations. This study focuses on a new lexicographical resource, named SemiMed, which addresses issues in wordlists and dictionaries arising from lexical ambiguity. Hsu’s (2013) Medical Word List (MWL), an academic list of semi-technical medical vocabulary, was selected as a starting point. A qualitative analysis underpinned by lexical semantic theories was conducted to analyse polysemes and homographs of MWL words. Then, a quantitative analysis that employed word sense disambiguation practices calculated MWL word meaning frequency. These analyses resulted in two key features, radial networks of meanings and technicality levels, that are expected to help SemiMed resolve issues in academic wordlists and conventional dictionaries caused by lexical ambiguity.

A controversial post by an X user regarding the sweetness level of a beverage sparked significant debate on social media. Public opinion was divided; some criticized the user for employing coarse language, while others defended the tweet as a factual description that should be viewed as constructive criticism of the brand. As the tweet could be perceived as offensive to the corporate entity, it raised concerns regarding its potential classification as defamatory speech. This study aims to identify and analyze the defamatory expressions within the tweets by the account from the perspective of forensic linguistics. The primary data source for this study was a specific post regarding a beverage variant from a popular brand in Indonesia. Data collection employed the documentation method utilizing the note-taking technique. Potentially defamatory expressions were analyzed through the theories of syntax, semantics, pragmatics, and discourse. The data were analyzed using a descriptive-qualitative approach. The results indicate that the post specifically targeted the corporate entity, as evidenced by the syntactic construction. Furthermore, the diction and phrasing employed carried pejorative and negative connotations. Although the post stemmed from the user's unpleasant experience after consuming the beverage, it exhibited elements of reputational injury, libel, and insult directed at the company. Consequently, the utterance warranted classification as defamatory speech.

This study uses deep learning, frame semantic theory, and precise hyperparameter tuning to classify social media hate speech. Three carefully selected hate speech datasets, arranged according to a frame semantic framework, are used to categorize opposing content, helping to better grasp context than simply looking for words. The Synthetic Minority Over-sampling Technique (SMOTE) enhanced minority-class detection to mitigate class imbalance. To find optimal configurations, deep learning architectures, activation functions, and data split algorithms were tested. The best approach used 70% of the data for training and 30% for testing, a model with hidden layers, a Rectifier activation function, and 10 epochs, achieving 96.30% accuracy, 96.95% recall, 99.15% precision, and 0.98 F1-score. These findings show that frame semantic theory, deep learning, and rigorous hyperparameter optimization can significantly improve social media hate speech detection systems. The method lays the foundation for context-aware and socially responsible content control.

Human languages differ widely, yet they share systematic regularities in the underlying semantic representations being expressed. How such similarities and differences arise remains unclear, in part because semantic theories often lack a principled link to neurocognitive constraints. Drawing on neurocognitive accounts in which semantic knowledge is grounded in biologically salient information dimensions, we examine how environmental factors shape conceptual representations in language. Here we show that word meanings across languages are organized along shared neurocognitive dimensions, while systematic variation along these dimensions is associated with climate. Using word embeddings from 53 languages and behavioral ratings from speakers of 8 languages, we find converging evidence that climatic variables explain semantic variation beyond commonly considered sociocultural factors. Complementary exploratory brain data further suggest climate-related modulation of activity patterns in the right anterior temporal lobe. Together, these findings indicate that semantic representations in language reflect biologically grounded dimensions that are flexibly shaped by long-term environmental conditions.

This study examines how effective Componential Analysis (CA), a classic semantic theory, can be used to analyze the many meanings of the English word “fuck”. Componential analysis breaks words into smaller parts called semantic components. The word “fuck” is a good test for this theory because it has a simple concrete meaning but is used in many different concrete and abstract ways. Using examples from the BFSU CQPweb corpus, the study first lists the main ways “fuck” is used. Then, it tries to break down each use into a set of components. The results show that CA works well for the simple, concrete meanings of “fuck,” such as its use for sex or damage. However, the components become too general and vague for uses where “fuck” is mainly used to express strong feelings. The study also notes some problems with the corpus and methods used, which affected the results. Beyond its theoretical evaluation, this analysis offers practical insights and suggests directions for further study. The findings imply that for language pedagogy, teaching a word like fuck effectively requires explicitly addressing its wide meanings and emotions, helping learners navigate its social impact. Methodologically, the challenges encountered, such as complex corpus queries and inconsistent data tagging, highlight the need for better technical training in corpus linguistics for students and researchers. Future research could build on this work by using larger spoken corpora or social media data to more fully capture informal and expressive uses, or by applying a similar analytical approach to other taboo words to test the generalizability of these findings.

Multiple representation theories of lexical semantics assume meaning is retrieved through simulation. However, simulation mechanisms are not well understood. Mental state inferencing - the capacity to understand mental states - has been proposed as a simulation mechanism, particularly for cognitive concepts (concepts referring to cognitive events, states, and products) (Kiefer et al., 2022). In a pre-registered study, we tested this proposal using an individual differences approach. Adult participants (n=297) completed three measures of mentalizing skills. They also completed two syntactic classification tasks (is this word a verb; is this word a noun?) to measure semantic processing and test for the cognition effect (more cognitive words processed more efficiently than less cognitive words). We replicated the cognition effect, with high-cognition words eliciting faster and more accurate responses than low-cognition words. Additionally, we found significant interactions between mentalizing and the cognition effect: participants with stronger mentalizing skills showed larger cognition effects. This relationship suggests that mentalizing may serve as a simulation mechanism when accessing word meaning.

This article presents an in-depth comparative analysis of the linguistic and cultural representation of the concept “goodness” in English and Uzbek languages. It explores how this moral category is expressed through vocabulary, idioms, and proverbs, and how these expressions reveal the cultural and ethical values of both nations. Drawing upon theories of conceptual linguistics and moral semantics, the paper discusses how language functions as a tool for reflecting and shaping moral thought. The findings demonstrate that English and Uzbek conceptualize goodness through different cultural lenses: English emphasizes personal virtue and ethical decision-making, while Uzbek foregrounds communal responsibility, empathy, and divine justice.

IntroductionThis study expands our understanding of neurogastronomy’s various dimensions and addresses a critical gap in the literature concerning its conceptual structure. However, as a field of research, neurogastronomy lacks conceptual clarity despite its growing popularity. Drawing on Semantic Network Theory, according to which cognitive associations define conceptual understanding, this study investigates the field’s cognitive structure.MethodsWord Association Tests were conducted with 327 gastronomy students in Turkey.ResultsThe analysis yielded 16 codes and 6 themes, with “sensory experience and taste perception” emerging as dominant. The findings demonstrate that neurogastronomy functions as a fragmented rather than a cohesive concept within the cognitive network.DiscussionBy empirically mapping the field’s conceptual boundaries, this study provides a foundation for clarifying terminology and informing future theoretical and applied research.

ABSTRACT Guiding tourist safety behaviour is pivotal in destination management. This study utilises Semantic Frame Theory (SFT) and Social Information Processing Theory (SIPT) to explore how the interaction between the semantic framing (suggestive vs. assertive) of service employees and tourism activity type (low-intensity vs. high-intensity) influences tourist safety behaviour. Four scenario-based experiments revealed that an assertive semantic frame paired with high-intensity activities increases perceived dependency, leading to greater safety behaviour. In contrast, suggestive semantic frames in low-intensity activities reduce perceived control, prompting compensatory safety behaviours. This research enriches the literature on semantic framing within the tourism domain and provides insights for formulating effective tourism safety communication strategies.

This paper examines the subtitle translation of the animated film The Secret Life of Pets from the perspective of Peter Newmark’s theories of communicative translation and semantic translation. The study reveals that the subtitle translation of this film embodies a combination of both principles. Most translations employ liberal translation through the conversion of cultural concepts, the use of Chinese idioms or idiomatic expressions, and contextual adaptation, reflecting the reader-centered equivalence principle of communicative translation. Some translations retain the original text structure, surface meaning, or cultural imagery through literal translation, demonstrating the text fidelity and author-centered principle of semantic translation. This research vividly illustrates the coexistence and complementarity of these two translation theories in practice.

Objective: This study aims to develop a religious text translation model based on rechecking semantic-communicative analysis to improve translation quality. The model supports semantic accuracy, cultural sensitivity, and moderation in line with the Sustainable Development Goals (SDGs). Theoretical framework: This research integrates semantic and communicative translation theory, cognitive-communicative approaches, functional translation principles, and hermeneutic interpretation. These frameworks collectively support a holistic and ethically grounded approach to religious translation. Literature review: Previous studies on religious translation focus mainly on isolated linguistic or cultural strategies, with limited integration of systematic rechecking and SDGs perspectives. This study addresses the gap by proposing an integrated semantic-communicative and contextual model. Methods: This study employs a qualitative approach using data from Islam: A Short History and focus group discussions with Qur’an translation teachers. Semantic-communicative analysis, rechecking procedures, and hermeneutic interpretation are applied to ensure accuracy and contextual relevance. Results: The findings indicate that religious text translation faces challenges related to semantic non-equivalence and cultural context. Integrating semantic-communicative analysis improves readability and meaning accuracy. Rechecking procedures effectively reduces the distortion of key religious terms. Implications: The study highlights the need for translator training that integrates linguistic and religious knowledge. It also supports the use of contextualized glossaries and cautious machine translation with rechecking mechanisms in line with the SDGs. Novelty: The novelty of this research lies in its holistic and replicable translation model integrating semantic-communicative analysis, expert-based rechecking, and hermeneutic interpretation. This approach advances translation studies by linking linguistic accuracy with ethical and sustainable knowledge transmission.

Semantic modeling has become one of the most productive methodological tools in contrastive lexicology because it allows researchers to formalize meaning, compare lexical systems across languages, and describe equivalence, partial equivalence, and lacunarity with higher precision than intuitive translation-based comparison. This article explores how semantic modeling can be applied to Uzbek and Russian lexical units by integrating componential analysis, semantic field theory, and frame-based representation. Relying on dictionary definitions and contextual evidence from digital corpora, the study demonstrates that contrasts between Uzbek and Russian are frequently shaped by differences in lexical segmentation, polysemy patterns, culturally salient frames, and the interaction between lexical meaning and grammatical expression. The results show that a combined semantic model (component + frame + distribution) improves the description of cross-linguistic correspondences, especially in domains where cultural experience is strongly encoded in the lexicon, such as kinship, social evaluation, and emotion concepts. The paper concludes that semantic modeling in contrastive lexicology is most effective when it treats meaning as a structured bundle of semantic components embedded in conventional frames and verified through corpus-based distributional evidence, rather than as a single “dictionary sense” matched to a translation equivalent.

This study reports the process of design of a Multimedia-Assisted Deep Learning (MADL) module for primary Chinese character learning, targeting the integration of pronunciation, shape, and meaning while cultivating critical thinking and problem-solving skills. Using a Design and Development Research (DDR) approach operationalized through the ADDIE model, the study intergrate Cognitive Theory of Multimedia Learning, Bloom’s Taxonomy, and cognitive semantic theory into concrete instructional decisions. This paper elaborates on the design of learning objectives and content, teaching strategies, multimeida materials, and assessment strategies. These components link radicals to contextualized reading–writing–meaning activities and higher-order tasks, ready for immediate classroom use. This paper contributes replicable, practical, and reusable design guidelines within a DDR/ADDIE–Design focus; a case module exemplifies the approach, comprising a teacher booklet and PPT materials aligned with the target texts.

Abstract: This article provides a novel interpretation of Nāgārjuna's Madhyamaka. I highlight what I take to be an unexamined presupposition shared by contemporary Madhyamaka scholars, that is, representationalism, in order to show how this assumption underpins ongoing debates over whether Nāgārjuna's thought is primarily "reason-driven" or principally "soteriologically-animated." Using a neopragmatist account of language, I trace scholarly debates over the metalinguistic function of Nāgārjuna's assertions and demonstrate representationalism's role in contemporary constructions of a Madhyamaka-friendly semantic theory. I argue that by explicitly rejecting representationalism, we can sidestep scholarly debates about truth and utility, as well as lay to rest concerns with the order of value between zetetic and protreptic techniques. Finally, through a comparison with Richard Rorty, I show that an anti-representationalist framework is implicit in Nāgārjuna's arguments. This, in turn, allows the problem of hypostatization to take center stage in the Madhyamaka message.

This research examines idiomatic expressions found in the humorous dialogues of Legally Blonde (2001) using Leech’s semantic theory. The study aims to identify the idioms used in the film, describe their meanings based on semantic interpretation, and explain how they contribute to humor. A descriptive qualitative method was applied, with the film script serving as the primary data source. The researcher carefully read the script, selected scenes containing humorous or informal conversations, and identified idioms spoken by the characters. Each idiom was then analyzed in context and categorized into four types: figurative, slang/colloquial, euphemistic, and hyperbolic. The findings reveal 17 idioms that support the film’s comedic tone. Slang and colloquial idioms appear most frequently, reflecting the informal and youthful atmosphere of the film. Figurative idioms express emotion and personality, euphemistic soften direct statements, and hyperbolic idioms create exaggerated effects that strengthen humor. Overall, the study shows that idioms not only function as linguistic expressions but also play an important role in developing character identity and enhancing the humorous style of the film

In-game puzzles are a core element in role-playing video games, commonly abbreviated as RPG. They have distinctive characteristics from general puzzles. This distinctiveness is perceived from how in-game puzzles influence and determine narrative and mechanical progressions of the players. In designing in-game puzzles, the designers have to consider the difficulty balance – the balance between clues and distractors. In this study, we propose what we call distractives, linguistic markers employed as a distractor in in-game puzzles. We employed the theories of frame semantics by Fillmore, ludic language for in-game puzzle designs by Purnama, Nababan, Santosa, and Purnomo, and bias language by Recasens, Danescu-Niculescu-Mizil and Jurafsky. Twelve RPGs were investigated to prove the presence of distractives. The findings indicate that distractives operate through framing by employing bias language to frame falsity as truth from which players are expected to be distracted. We further classified the framing acts into causal, chronological, conditional, directional, reciprocal, reflectional and representational framings. Game developers could employ this typology as a guideline to balance the difficulty of distractives for in-game puzzles in role-playing video games. Future studies could employ distractives as a theoretical basis for investigating distractives as a speech act in the context of in-game puzzle design.

This study aims to describe the variations in the use of the word "keadaan" ("state") in news about the DPR's demands demonstration and to map its meaning categories based on the Natural Semantic Metalanguage (MSA) approach. This study uses a qualitative method with documentation techniques on online news texts containing the word "keadaan" ("state") and collected from various national news portals during the period of August–September 2025. The analysis was carried out in three stages: data reduction, data presentation, and drawing conclusions based on the Natural Semantic Metalanguage theory of Wierzbicka and Goddard (2014). The results of the study found 20 words variations that represent five main categories of meaning of "keadaan" ("state"): stable and positive states, negative and chaotic states, states of density/mobility, psychological/emotional states, and uncertain states. The dominant semantic primes are PEOPLE, HAPPEN, and GOOD/BAD. This study confirms that the MSA approach is effective in explaining the meaning of state words in a simple but profound way, while at the same time shows that media language shapes socio political perceptions through lexical choices