The nature of abstract and concrete semantics and differences between them have remained a debated issue in psycholinguistic and cognitive studies for decades. Most of the available behavioral and neuroimaging studies reveal distinctions between these two types of semantics, typically associated with a so-called “concreteness effect.” Many attempts have been made to explain these differences using various approaches, from purely theoretical linguistic and cognitive frameworks to neuroimaging experiments. In this brief overview, we will try to provide a snapshot (...) of these diverse views and relationships between them and highlight the crucial issues preventing this problem from being solved. We will argue that one potentially beneficial way forward is to identify the neural mechanisms underpinning acquisition of the different types of semantics (e.g., by using neurostimulation techniques to establish causal relationships), which may help explain the distinctions found between the processing of concrete and abstract semantics. (shrink)

Solutions to word problems are moderated by the semantic alignment of real-world relations with mathematical operations. Categorical relations between entities are aligned with addition, whereas certain functional relations between entities are aligned with division. Similarly, discreteness vs. continuity of quantities is aligned with different formats for rational numbers. These alignments have been found both in textbooks and in the performance of college students in the USA and in South Korea. The current study examined evidence for alignments in Russia. Textbook analyses (...) revealed semantic alignments for arithmetic word problems, but not for rational numbers. Nonetheless, Russian college students showed semantic alignments both for arithmetic operations and for rational numbers. Since Russian students exhibit semantic alignments for rational numbers in the absence of exposure to examples in school, such alignments likely reflect intuitive understanding of mathematical representations of real-world situations. (shrink)

The present article is devoted to a logical inquiry on the notions of permanence and termination, which play a central role in many areas of temporal reasoning. In the first part, we introduce a bimodal framework to represent these notions and provide a syntactic and semantic comparison with a monomodal framework representing the notion of future necessity. In the second part, we focus on the problem of defining synonymous logical systems over the two frameworks; as an example, we provide an (...) extended analysis of two systems, the monomodal K4 and the bimodal S4X. The third part of the article indicates possible developments of the proposed line of inquiry, such as finding a simple representation in the bimodal language of some interesting properties of time and identifying further pairs of synonymous systems. (shrink)

Many recent experiments have used parallel Implicit Association Test (IAT) and selfreport measures of attitudes. These measures are sometimes strongly correlated. However, many of these studies find apparent dissociations in the form of (a) weak correlations between the two types of measures, (b) separation of their means on scales that should coincide if they assess the same construct, or (c) differing correlations with other variables. Interpretations of these empirical patterns are of three types: single-representation — the two types of measures (...) assess a single attitude, but under the influence of different extra-attitudinal process influences; dual-representation — the two types of measures assess distinct forms of attitudes (e.g., conscious vs. unconscious; implicit vs. explicit); and person vs. culture — a variant of the dualrepresentation view in which self-report measures reflect personal attitudes, whereas IAT measures reflect non-attitudinal cultural or semantic knowledge. Proponents sometimes interpret evidence for single versus dual constructs as evidence for single versus dual structural representations. Behavioral evidence can establish the discriminant validity of implicit and explicit attitude phenomena (dual constructs), but cannot choose among single- vs. dual-representation interpretations because the distinct constructs remain susceptible to interpretation in terms of either one or two representations. Selecting among representational accounts must therefore be based on considerations of explanatory power or parsimony. (shrink)

This book attempts to marry truth-conditional semantics with cognitive linguistics in the church of computational neuroscience. To this end, it examines the truth-conditional meanings of coordinators, quantifiers, and collective predicates as neurophysiological phenomena that are amenable to a neurocomputational analysis. Drawing inspiration from work on visual processing, and especially the simple/complex cell distinction in early vision (V1), we claim that a similar two-layer architecture is sufficient to learn the truth-conditional meanings of the logical coordinators and logical quantifiers. As a (...) prerequisite, much discussion is given over to what a neurologically plausible representation of the meanings of these items would look like. We eventually settle on a representation in terms of correlation, so that, for instance, the semantic input to the universal operators (e.g. and, all)is represented as maximally correlated, while the semantic input to the universal negative operators (e.g. nor, no)is represented as maximally anticorrelated. On the basis this representation, the hypothesis can be offered that the function of the logical operators is to extract an invariant feature from natural situations, that of degree of correlation between parts of the situation. This result sets up an elegant formal analogy to recent models of visual processing, which argue that the function of early vision is to reduce the redundancy inherent in natural images. Computational simulations are designed in which the logical operators are learned by associating their phonological form with some degree of correlation in the inputs, so that the overall function of the system is as a simple kind of pattern recognition. Several learning rules are assayed, especially those of the Hebbian sort, which are the ones with the most neurological support. Learning vector quantization (LVQ) is shown to be a perspicuous and efficient means of learning the patterns that are of interest. We draw a formal parallelism between the initial, competitive layer of LVQ and the simple cell layer in V1, and between the final, linear layer of LVQ and the complex cell layer in V1, in that the initial layers are both selective, while the final layers both generalize. It is also shown how the representations argued for can be used to draw the traditionally-recognized inferences arising from coordination and quantification, and why the inference of subalternacy breaks down for collective predicates. Finally, the analogies between early vision and the logical operators allow us to advance the claim of cognitive linguistics that language is not processed by proprietary algorithms, but rather by algorithms that are general to the entire brain. Thus in the debate between objectivist and experiential metaphysics, this book falls squarely into the camp of the latter. Yet it does so by means of a rigorous formal, mathematical, and neurological exposition – in contradiction of the experiential claim that formal analysis has no place in the understanding of cognition. To make our own counter-claim as explicit as possible, we present a sketch of the LVQ structure in terms of mereotopology, in which the initial layer of the network performs topological operations, while the final layer performs mereological operations. The book is meant to be self-contained, in the sense that it does not assume any prior knowledge of any of the many areas that are touched upon. It therefore contains mini-summaries of biological visual processing, especially the retinocortical and ventral /what?/ parvocellular pathways computational models of neural signaling, and in particular the reduction of the Hodgkin-Huxley equations to the connectionist and integrate-and-fire neurons Hebbian learning rules and the elaboration of learning vector quantization the linguistic pathway in the left hemisphere memory and the hippocampus truth-conditional vs. image-schematic semantics objectivist vs. experiential metaphysics and mereotopology. All of the simulations are implemented in MATLAB, and the code is available from the book’s website. • The discovery of several algorithmic similarities between visison and semantics. • The support of all of this by means of simulations, and the packaging of all of this in a coherent theoretical framework. (shrink)

Semantic priming has been a focus of research in the cognitive sciences for more than 30 years and is commonly used as a tool for investigating other aspects of perception and cognition, such as word recognition, language comprehension, and knowledge representations. Semantic Priming: Perspectives from Memory and Word Recognition examines empirical and theoretical advancements in the understanding of semantic priming, providing a succinct, in-depth review of this important phenomenon, framed in terms of models of memory and models of word recognition. (...) The first section examines models of semantic priming, including spreading activation models, the verification model, compound-cue models, distributed network models, and multistage activation models (e.g. interactive-activation model). The second section examines issues and findings that have played an especially important role in testing models of priming and includes chapters on the following topics: methodological issues (e.g. counterbalancing of materials, choice of priming baselines); automatic vs. strategic priming; associative vs. "pure" semantic priming; mediated priming; long-term semantic priming; backward priming; unconscious priming; the prime-task effect; list context effects; effects of word frequency, stimulus quality, and stimulus repetition; and the cognitive neuroscience of semantic priming. The book closes with a summary and a discussion of promising new research directions. The volume will be of interest to a wide range of researchers and students in the cognitive sciences and neurosciences. (shrink)

This paper argues in the first place that nominalists are right in insisting against ontological realists that semantic universality does not require commitment to universal entities. However, Ockham, in his zeal to get rid of Scotus’s universal entities, swept under the carpet the issue of universal representational content of genuinely universal symbols, conflating it with the mere indifference of the information content of non-distinctive singular representations. Buridan did come up with an abstractionist theory of the formation of genuinely universal (...) representational content to solve the resulting issues, however, the paper argues further, his solution is committed to attributing the sort of “aspectuality” to universal absolute concepts that his Ockhamist semantics denies to them. The conclusion of the paper suggests how Aquinas’s “moderate realism” can provide a consistent solution without the ontological extravaganza of ontological realists, without conflating the mere indifference of singular representation with genuine universality, and without having to deny aspectuality to our quidditative universal concepts formed by abstraction. (shrink)

Word co‐occurrence patterns in language corpora contain a surprising amount of conceptual knowledge. Large language models (LLMs), trained to predict words in context, leverage these patterns to achieve impressive performance on diverse semantic tasks requiring world knowledge. An important but understudied question about LLMs’ semantic abilities is whether they acquire generalized knowledge of common events. Here, we test whether five pretrained LLMs (from 2018's BERT to 2023's MPT) assign a higher likelihood to plausible descriptions of agent−patient interactions than to minimally (...) different implausible versions of the same event. Using three curated sets of minimal sentence pairs (total n = 1215), we found that pretrained LLMs possess substantial event knowledge, outperforming other distributional language models. In particular, they almost always assign a higher likelihood to possible versus impossible events (The teacher bought the laptop vs. The laptop bought the teacher). However, LLMs show less consistent preferences for likely versus unlikely events (The nanny tutored the boy vs. The boy tutored the nanny). In follow‐up analyses, we show that (i) LLM scores are driven by both plausibility and surface‐level sentence features, (ii) LLM scores generalize well across syntactic variants (active vs. passive constructions) but less well across semantic variants (synonymous sentences), (iii) some LLM errors mirror human judgment ambiguity, and (iv) sentence plausibility serves as an organizing dimension in internal LLM representations. Overall, our results show that important aspects of event knowledge naturally emerge from distributional linguistic patterns, but also highlight a gap between representations of possible/impossible and likely/unlikely events. (shrink)

We present the results of four experiments concerning the evaluation people make of sentences involving “many”, showing that two sentences of the form “many As are Bs” vs. “many As are Cs” need not be equivalent when evaluated relative to a background in which B and C have the same cardinality and proportion to A, but in which B and C are predicates with opposite semantic and affective values. The data provide evidence that subjects lower the standard relevant to ascribe (...) “many” for the more negative predicate, and that judgments involving “many” are sensitive to moral considerations, namely to expectations involving a representation of the desirability as opposed to the mere probability of an outcome. We relate the results to similar semantic asymmetries discussed in the psychological literature, in particular to the Knobe effect and to framing effects. (shrink)

Cognition is both empowered and limited by representations. The matrix lens model explicates tasks that are based on frequency counts, conditional probabilities, and binary contingencies in a general fashion. Based on a structural analysis of such tasks, the model links several problems and semantic domains and provides a new perspective on representational accounts of cognition that recognizes representational isomorphs as opportunities, rather than as problems. The shared structural construct of a 2 × 2 matrix supports a set of (...) generic tasks and semantic mappings that provide a unifying framework for understanding problems and defining scientific measures. Our model's key explanatory mechanism is the adoption of particular perspectives on a 2 × 2 matrix that categorizes the frequency counts of cases by some condition, treatment, risk, or outcome factor. By the selective steps of filtering, framing, and focusing on specific aspects, the measures used in various semantic domains negotiate distinct trade-offs between abstraction and specialization. As a consequence, the transparent communication of such measures must explicate the perspectives encapsulated in their derivation. To demonstrate the explanatory scope of our model, we use it to clarify theoretical debates on biases and facilitation effects in Bayesian reasoning and to integrate the scientific measures from various semantic domains within a unifying framework. A better understanding of problem structures, representational transparency, and the role of perspectives in the scientific process yields both theoretical insights and practical applications. (shrink)

Sentence comprehension involves maintaining and continuously integrating linguistic information and, thus, makes demands on working memory. Past research has demonstrated that semantic WM, but not phonological WM, is critical for integrating word meanings across some distance and resolving semantic interference in sentence comprehension. Here, we examined the relation between phonological and semantic WM and the comprehension of center-embedded relative clause sentences, often argued to make heavy demands on WM. Additionally, we examined the relation between phonological and semantic WM and the (...) comprehension of transitive and dative active and passive sentences, which may also draw on WM resources depending on the number of propositions that must be maintained and the difficulty of processing passive clauses. In a large sample of individuals with aphasia, we assessed whether comprehension performance on more complex vs. simpler active-passive or embedded relative clause sentences would be predicted by semantic but not phonological WM when controlling for single word comprehension. For performance on the active-passive comprehension task, we found that semantic WM, but not phonological WM, predicted comprehension of dative sentences when controlling for comprehension of transitive sentences. We also found that phonological WM, but not semantic WM, predicted mean comprehension for reversible active-passive sentences when controlling for trials with lexical distractors. On the relative clause comprehension task, consistent with prior results, we found that semantic WM, but not phonological WM, predicted comprehension of object relative clause sentences and relative clause sentences with a passive construction. However, both phonological WM and semantic WM predicted mean comprehension across all relative clause types for reversible trials when controlling for trials with lexical distractors. While we found evidence of semantic WM’s role in comprehension, we also observed unpredicted relations between phonological WM and comprehension in some conditions. Post-hoc analyses provided preliminary evidence that phonological WM maintains a backup phonological representation of the sentence that may be accessed when sentence comprehension processing is less efficient. Future work should investigate possible roles that phonological WM may play across sentence types. (shrink)

Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical) senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6–12 short phrases containing a polysemous word in literal, metonymic, or (...) metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while metaphorical senses are stored separately; in adjectives, metonymic senses significantly overlap with both literal and metaphorical senses. (shrink)

The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation (“bat”, in a baseball vs. a vampire context), as (...) well as more nuanced differences of meaning—for example, polysemous words such as “book”, which can be interpreted in distinct but related senses (“explain a book”, information, vs. “open a book”, object) whose differences are fine‐grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb‐noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine‐grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness. (shrink)

Much research on color representation and categorization has assumed that relations among color terms can be proxies for relations among color percepts. We test this assumption by comparing the mapping of color words with color appearances among different observer groups performing cognitive tasks: an invariance of naming task; and triad similarity judgments of color term and color appearance stimuli within and across color categories. Observer subgroups were defined by perceptual phenotype and photopigment opsin genotype analyses. Results suggest that individuals rely (...) on at least two different representational models of color experience: one lexical, conforming to the culture's normative linguistic representation, and another individual perceptual representation organizing each observer's color sensation experiences. Additional observer subgroup analyses suggest that perceptual phenotype variation within a language group may play a greater role in the shared color naming system than previously thought. A reexamination of color naming data in view of these findings may reveal influences on color naming important to current theories. (shrink)

Regular polysemes are sets of ambiguous words that all share the same relationship between their meanings, such as CHICKEN and LOBSTER both referring to an animal or its meat. To probe how a distributional semantic model, here exemplified by bidirectional encoder representations from transformers (BERT), represents regular polysemy, we analyzed whether its embeddings support answering sense analogy questions similar to “is the mapping between CHICKEN (as an animal) and CHICKEN (as a meat) similar to that which maps between LOBSTER (as (...) an animal) to LOBSTER (as a meat)?” We did so using the LRcos model, which combines a logistic regression classifier of different categories (e.g., animal vs. meat) with a measure of cosine similarity. We found that (a) the model was sensitive to the shared structure within a given regular relationship; (b) the shared structure varies across different regular relationships (e.g., animal/meat vs. location/organization), potentially reflective of a “regularity continuum;” (c) some high-order latent structure is shared across different regular relationships, suggestive of a similar latent structure across different types of relationships; and (d) there is a lack of evidence for the aforementioned effects being explained by meaning overlap. Lastly, we found that both components of the LRcos model made important contributions to accurate responding and that a variation of this method could yield an accuracy boost of 10% in answering sense analogy questions. These findings enrich previous theoretical work on regular polysemy with a computationally explicit theory and methods, and provide evidence for an important organizational principle for the mental lexicon and the broader conceptual knowledge system. (shrink)

I defend a semantic theory of quotation marks, according to which these are ambiguous, as they have several different acceptations involving corresponding different conventional indications. In particular, in allusion (“mixed”) uses, the corresponding conventional indication is one with an adverbial or prepositional content, roughly equivalent to “using the quoted expression or an appropriate version of it”. And in “scare” uses, the corresponding conventional indication is that the enclosed expression should be used not plainly but in some broadly speaking distanced way, (...) or that it is being so used by the utterer. I also defend this view against some alternative views on which allusion and distance indications are to be seen as pragmatically conveyed. In particular, I consider several views that attempt to explain especially allusion and distance indications as pragmatic suggestions generated from a meager conventional basis, and I argue that they cannot accommodate a number of linguistic phenomena and reflectively supported theses about the use of quotation marks. I lay special emphasis on the fact that the main pragmatic theories fail to pass an extremely plausible test for challenges to polysemic accounts of an expression. (shrink)

This volume is the first to focus specifically on experimental studies of the semantics of gradability, scale structure and vagueness. It presents support for and challenges to current formal analyses of these phenomena in view of experimentally collected data, highlighting the ways semantic and pragmatic theory can benefit from experimental methodologies. The papers in the volume contribute to an explicit and detailed account of the use, representation, and online processing of gradable and vague expressions using various kinds of controlled (...) speaker judgment tasks, eye tracking, and ERP. The aim is to strengthen the foundations of experimental semantics and promote interaction between linguists, psycholinguists, psychologists, and philosophers who are interested in the semantics of natural language. Using data representing different languages and a variety of nominal and adjectival constructions, including degree modification and comparatives, the contributions address scale-based classifications of gradable predicates, such as the absolute vs. relative distinction; the nature of the standards for applicability of gradable expressions and the ways in which standards are determined; the nature of dimensions and multidimensionality in the meaning of scalar expressions; and the role of embodiment, subjectivity, and sociolinguistic considerations in the use and understanding of gradable expressions. (shrink)

Applying machine learning algorithms to automatically infer relationships between concepts from large-scale collections of documents presents a unique opportunity to investigate at scale how human semantic knowledge is organized, how people use it to make fundamental judgments (“How similar are cats and bears?”), and how these judgments depend on the features that describe concepts (e.g., size, furriness). However, efforts to date have exhibited a substantial discrepancy between algorithm predictions and human empirical judgments. Here, we introduce a novel approach to generating (...) embeddings for this purpose motivated by the idea that semantic context plays a critical role in human judgment. We leverage this idea by constraining the topic or domain from which documents used for generating embeddings are drawn (e.g., referring to the natural world vs. transportation apparatus). Specifically, we trained state-of-the-art machine learning algorithms using contextually-constrained text corpora (domain-specific subsets of Wikipedia articles, 50+ million words each) and showed that this procedure greatly improved predictions of empirical similarity judgments and feature ratings of contextually relevant concepts. Furthermore, we describe a novel, computationally tractable method for improving predictions of contextually-unconstrained embedding models based on dimensionality reduction of their internal representation to a small number of contextually relevant semantic features. By improving the correspondence between predictions derived automatically by machine learning methods using vast amounts of data and more limited, but direct empirical measurements of human judgments, our approach may help leverage the availability of online corpora to better understand the structure of human semantic representations and how people make judgments based on those. (shrink)

We examine the interrelationships between analog computational modelling and analogue (physical) modelling. To this end, we attempt a regimentation of the informal distinction between analog and digital, which turns on the consideration of computing in a broader context. We argue that in doing so one comes to see that (scientific) computation is better conceptualised as an epistemic process relative to agents, wherein representations play a key role. We distinguish between two, conceptually distinct, kinds of representation that, we argue, are both (...) involved in each case of computing. Based on the semantic and syntactic properties of each of these representations, we put forward a new account of the distinction between analog and digital computing. We discuss how the developed account is able to explain various properties of different models of computation, and we finish by conceptually comparing analog computational modelling to analogue (scale) modelling. It is concluded that, contrary to the standard view, the two practices are orthogonal, differing both in their foundations and in the epistemic functions they fulfil. (shrink)

The mainstream philosophical approach to inference, which insists on sentence-like representations and a linguistic capability, excludes non-human animals as possible agents capable of making inferences. However, an abundance of studies show that many animal species exhibit behaviors that seem to rely on some kind of reasoning. My focus here are the transitive inference tasks, which most species solve quite successfully. These findings put pressure on the mainstream views, and still lack a convincing explanation. I introduce the concept of affective representations, (...) which satisfy the semantic and structural requirements for participating in inferences. I also argue for a broader conception of inference, and show how we can apply this view to explain the results of the transitive inference studies. Finally, I suggest it is more useful to think of flexibility of thought in terms of a continuous range, rather than a dichotomy of flexible vs. inflexible. (shrink)

Leading scholars in the philosophy of language and theoretical linguistics present brand-new papers on a major topic at the intersection of the two fields, the distinction between semantics and pragmatics. Anyone engaged with this issue in either discipline will find much to reward their attention here. Contributors: Kent Bach, Herman Cappelen, Michael Glanzberg, Jeffrey C. King, Ernie Lepore, Stephen Neale, F. Recanati, Nathan Salmon, Mandy Simons, Scott Soames, Robert J. Stainton, Jason Stanley, Zoltan Gendler Szabo.

I defend a conception of Logic as normative for the sort of activities in which inferences super-vene, namely, reasoning and arguing. Toulmin’s criticism of formal logic will be our framework to shape the idea that in order to make sense of Logic as normative, we should con-ceive it as a discipline devoted to the layout of arguments, understood as the representations of the semantic, truth relevant, properties of the inferences that we make in arguing and reason-ing.

Silent gesture is not considered to be linguistic, on par with spoken and sign languages. It is claimed that silent gestures, unlike language, represent events holistically, without compositional structure. However, recent research has demonstrated that gesturers use consistent strategies when representing objects and events, and that there are behavioral and clinically relevant limits on what form a gesture may take to effect a particular meaning. This systematicity challenges a holistic interpretation of silent gesture, which predicts that there should be no (...) stable form‐meaning correspondence across event representations. Here, we demonstrate to the contrary that untrained gesturers systematically manipulate the form of their gestures when representing events with and without a theme (e.g., Someone popped the balloon vs. Someone walked), that is, transitive and intransitive events. We elicited silent gestures and annotated them for manual features active in coding transitivity distinctions in sign languages. We trained linear support vector machines to make item‐by‐item transitivity predictions based on these features. Prediction accuracy was good across the entire dataset, thus demonstrating that systematicity in silent gesture can be explained with recourse to subunits. We argue that handshape features are constructs co‐opted from cognitive systems subserving manual action production and comprehension for communicative purposes, which may integrate into the linguistic system of emerging sign languages. We further suggest that nonsigners tend to map event participants to each hand, a strategy found across genetically and geographically distinct sign languages, suggesting the strategy's cognitive foundation. (shrink)

Pour la plupart des systèmes de représentation de la connaissance orientés concept, l’un des problèmes principaux relève de la commodité technique. A savoir, la représentation de connaissance en termes prototypiques, tout comme la possibilité d’exploiter des formes de raisonnement conceptuel basées sur la typicalité, ne sont pas autorisées. Au contraire, dans les sciences cognitives, il existe des données en faveur de concepts prototypiques, et des formes non-monotoniques de raisonnement conceptuel ont été largement étudiées. Ce fossé cognitif concernant la représentation et (...) le raisonnement constitue un problème pour les systèmes computationnels, puisque l’information prototypique joue un rôle crucial dans plusieurs tâches importantes. Dans la lignée des théories du raisonnement et de la rationalité dites du double processus, nous soutenons que la représentation conceptuelle dans les systèmes computationnels devrait dépendre de (au moins) deux composantes représentationnelles, chacune spécialisée dans le traitement de différents genres de processus de raisonnement. Dans cet article, nous présentons les avantages computationnels de cette approche en termes de double processus, et les comparons brièvement avec d’autres solutions d’orientation logique, adoptées pour traiter du même problème. (shrink)

A constitutive theory of representation must address two challenges. The content determination challenge requires specifying why a particular state has a given content. The job description challenge requires spelling out the explanatory role that representational notions play in that theory. Recently, Nicholas Shea has advanced *varitel semantics* as a hybrid approach to representation to answer those challenges, supplementing teleosemantics with non-historical features –namely, exploitable relations and robustness. In this paper, I critically assess the hybrid theory’s answers to both (...) challenges, arguing that their hybrid nature undermines their merits. In each case, I will show that it is hard to establish how the alleged complementariness of the hybrid account components works. I will conclude that internal problems beset Shea’s theory of representation. (shrink)

It has long ben recognised that there are referential uses of definite descriptions. It is not as widely recognised that there are atttributives uses of idexicals and other such paradigmatically singular terms. I offer an account of the referential/attributive distinction which is intended to give a unified treatment of both sorts of cases. I argue that the best way to account for the referential/attributive distinction is to treat is as semantically underdetermined which sort of propositions is expressed in a context. (...) In certain contexts the proposition expressed will be a descriptive one, and in others it will be an object-dependent one. I appeal to Sperer and Wilson's (1986) idea that the recovery of the content of an utterance involves pragmatic processes of enrichment of a representation of the logical form of utterance. According to the account I offer, the first-level descriptive meaning associated with an expression (whether this is an indexical or a definite description) is pragmatically enriched and then used either to track an individual in the context, or is taken to lay down a condition of satisfaction for an individual. The proposition that the listener takes the speaker to have expressed is recovered on the basis of considerations of relevance and contextually available information about the speaker's directive intentions. Although my account has affinities with those of Recanati (1993) and Nunberg (1993), it also differs from theirs in crucial ways. Each of these authors sees asymmetries where I see none. I give reasons for preferring my symmetrical account. (shrink)

The paper describes an algorithm for semantic representation of behavioral contexts relative to a dichotomic decision alternative. The contexts are represented as quantum qubit states in two-dimensional Hilbert space visualized as points on the Bloch sphere. The azimuthal coordinate of this sphere functions as a one-dimensional semantic space in which the contexts are accommodated according to their subjective relevance to the considered uncertainty. The contexts are processed in triples defined by knowledge of a subject about a binary situational factor. The (...) obtained triads of context representations function as stable cognitive structure at the same time allowing a subject to model probabilistically-variative behavior. The developed algorithm illustrates an approach for quantitative subjectively-semantic modeling of behavior based on conceptual and mathematical apparatus of quantum theory. (shrink)

In his latest book, Frank Ankersmit proposes an original theory of historical representation. In this review I focus on what I take to be his most important semantic points with respect to representation, meaning, truth, and reference. First, I provide a short summary of the book. Second, I explore his semantics in terms of aspects and compare it with a different account inspired by the Fregean notion of mode of presentation. As my examination shows, Ankersmit’s analysis faces the problem (...) of “loosing indirectness” and, moreover, there seems to exist an alternative and plausible view that does not suffer from this problem. Finally, I conclude with a couple of comments on the Copernican Revolution advocated in the book. (shrink)

The specific goal of the article is to investigate the principles governing the perception of rhythmic structure in dance and music—taken separately and together—on the basis of a case study. I take as a starting point Lerdahl and Jackendoff’s (A generative theory of tonal music. MIT Press, 1983) conception of musical rhythm as the interaction between grouping and meter, and I examine to what extent it can apply to dance. Then, I explore how the rhythmical structures of music and dance (...) interact in a single event. I conclude that dance and music perception largely share the same abstract system, and the differences in the properties of their structure derives from the different (visual vs. auditory) modalities in which they are perceived; their modality difference also affects the perceived structure resulting from their combination in dance-music events. The exploration is guided by a detailed examination of the opening of Stravinsky’s _Augurs of Spring_ (1913) as choreographed by Nijinsky (1913), Béjart (1970) and Bausch (1975). By comparing these minimal pairs of dance-music events, I adapt the formal methodology of linguistics to other cognitive systems. The general goal of the article is to shed further light on the organizational principles of mental representations by comparing several cognitive systems in order to distinguish between general cognitive properties and modality-specific or domain-specific properties. (shrink)

How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and (...) anyone interested in the development of computational semantics. (shrink)

This paper embeds the core part of Discourse Representation Theory in the classical theory of types plus a few simple axioms that allow the theory to express key facts about variables and assignments on the object level of the logic. It is shown how the embedding can be used to combine core analyses of natural language phenomena in Discourse Representation Theory with analyses that can be obtained in Montague Semantics.

The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called “semantic pointers.” Semantic pointers are symbol-like representations that (...) result from the compression and recursive binding of perceptual, lexical, and motor representations, effectively integrating traditional connectionist and symbolic approaches. We present a computational model using semantic pointers that replicates experimental data from categorization studies involving each prior paradigm. We argue that a framework involving semantic pointers can provide a unified account of conceptual phenomena, and we compare our framework to existing alternatives in accounting for the scope, content, recursive combination, and neural implementation of concepts. (shrink)

The paper develops some of the conclusions, reached in Floridi (2007), concerning the future developments of Information and Communication Technologies (ICTs) and their impact on our lives. The two main theses supported in that article were that, as the information society develops, the threshold between online and offline is becoming increasingly blurred, and that once there won't be any significant difference, we shall gradually re-conceptualise ourselves not as cyborgs but rather as inforgs, i.e. socially connected, informational organisms. In this paper, (...) I look at the development of the so-called Semantic Web and Web 2.0 from this perspective and try to forecast their future. Regarding the Semantic Web, I argue that it is a clear and well-defined project, which, despite some authoritative views to the contrary, is not a promising reality and will probably fail in the same way AI has failed in the past. Regarding Web 2.0, I argue that, although it is a rather ill-defined project, which lacks a clear explanation of its nature and scope, it does have the potentiality of becoming a success (and indeed it is already, as part of the new phenomenon of Cloud Computing) because it leverages the only semantic engines available so far in nature, us. I conclude by suggesting what other changes might be expected in the future of our digital environment. (shrink)

This paper examines the stage-level/individual-level hypothesis (Kratzer 1989; Diesing 1988) from the point of view of modern Scottish Gaelic. This language exhibits two syntactically distinct predicational structures, and in particular, two distinct subject positions distinguishable on the basis of word order. While the distinction between the two positions can be shown to support the stage/individual-level hypothesis in one sense, the picture is muddied by the fact that many habitual or ‘characteristic’ sentences seem to be formed according to the stage-level subject (...) construction type.The solution proposed relies on two novel elements. First, it distinguishes the classical Davisonian event variable from the Kratzerian one hypothesized to be the hallmark of the stage-level sentence type. And secondly, it makes a strict logical separation between two types of generics: generics proper, which involve quantifying over an individual variable; and habituals, which only involve quantification over an event variable. These are represented by two distinct logical types which may nevertheless give rise to similar truth conditions in context.I show that the analysis can be made to account for tense interpretation, the scope of genericity, and the facts of syntactic complementation in Scottish Gaelic. To the extent that the solution is successful, it is evidence for a quite direct mapping between syntactic and semantic representations and for the important intuitions behind the initial Kratzer/Diesing stage vs. individual-level hypothesis. (shrink)

Computational models of semantic memory exploit information about co-occurrences of words in naturally occurring text to extract information about the meaning of the words that are present in the language. Such models implicitly specify a representation of temporal context. Depending on the model, words are said to have occurred in the same context if they are presented within a moving window, within the same sentence, or within the same document. The temporal context model (TCM), which specifies a particular definition of (...) temporal context, has proved useful in the study of episodic memory. The predictive temporal context model (pTCM) uses the same definition of temporal context to generate semantic memory representations. Taken together pTCM and TCM may prove to be part of a general model of declarative memory. (shrink)

Self-knowledge is knowledge of one’s own states (or processes) in an indexical mode of presentation. The philosophical debate is concentrating on mental states (or processes). If we characterize self-knowledge by natural language sentences, the most adequate utterance has a structure like “I know that I am in mental state M”. This common sense characterization has to be developed into an adequate description. In this investigation we will tackle two questions: (i) What precisely is the phenomenon referred to by “self-knowledge” and (...) how can we adequately describe a form of self-knowledge which we might realistically enjoy? (ii) Can we have self-knowledge given the fact that the meaning of some words which we utter depends on the environment or the speech community? The theory we defend argues that we have to distinguish the public meaning of utterances, on the one hand, and the mental representations which are constituting a mental state of an individual, on the other. Self-knowledge should be characterized on the level of mental representations while the semantics of utterances self-attributing mental states should be treated separately. Externalism is only true for the public meaning of utterances but not for beliefs and other mental states including self-knowledge. (shrink)

SEMANTIC ARITHMETIC: A PREFACE John Corcoran Abstract Number theory, or pure arithmetic, concerns the natural numbers themselves, not the notation used, and in particular not the numerals. String theory, or pure syntax, concems the numerals as strings of «uninterpreted» characters without regard to the numbe~s they may be used to denote. Number theory is purely arithmetic; string theory is purely syntactical... in so far as the universe of discourse alone is considered. Semantic arithmetic is a broad subject which begins when (...) numerals are mentioned (not just used) and mentioned as names of numbers (not just as syntactic objects). Semantic arithmetic leads to many fascinating and surprising algorithms and decision procedures; it reveals in a vivid way the experiential import of mathematical propositions and the predictive power of mathematical knowledge; it provides an interesting perspective for philosophical, historical, and pedagogical studies of the growth of scientific knowledge and of the role metalinguistic discourse in scientific thought. (shrink)

This book is a study of the second-edition version of the 'Transcendental Deduction', which is one of the most important and obscure sections of Kant's Critique of Pure Reason. By way of a close analysis of the B-Deduction, Adam Dickerson makes the distinctive claim that the Deduction is crucially concerned with the problem of making intelligible the unity possessed by complex representations - a problem that is the representationalist parallel of the semantic problem of the unity of the proposition. Along (...) the way he discusses most of the key themes in Kant's theory of knowledge, including the nature of thought and representation, the notion of objectivity, and the way in which the mind structures our experience of the world. (shrink)

This volume is a collection of new and previously published essays focusing on one of the most exciting and actively discussed topics in contemporary philosophy: naturalistic theories of mental content. The volume brings together important papers written by some of the most distinguished theorists working in the field today. Authors contributing to the volume include Jerry Fodor, Ruth Millikan, Fred Dretske, Ned Block, Robert Cummins, and Daniel Dennett.

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9‐year‐old children. The neural network was trained and validated in the child semantic space. (...) Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed‐effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed. (shrink)

In this thesis, Semantics, Meta-Semantics, and Ontology, I provide a critique of the method of truth in metaphysics. Davidson has suggested that we can determine the metaphysical nature and structure of reality through semantic investigations. By contrast, I argue that it is not semantics, but meta-semantics, which reveals the metaphysically necessary and sufficient truth conditions of our claims. As a consequence I reject the Quinean criterion of ontological commitment. In Part I, chapter 1, I argue that (...) the metaphysically primary truth bearers are not propositions, but rather concrete representations, either beliefs or sentences. I show, in chapter 2, that we can give sense to a truth predicate applying to sentences, given a truth operator and quantification into sentence position. I argue that this strategy does not commit us to the existence of propositions serving as truth bearers. In Part II I argue that although we must assign semantic values to sentences and/or predicates, the meaningfulness of these expressions is not thereby explained. In chapter 3 I articulate Davidson’s problem of predication and his solution, but argue that he was wrong to attribute this solution to Tarski. In chapter 4 I examine the semantics of modal languages; I conclude that although they require semantic values for predicates and/or sentences we should be instrumentalists about these theories. In Part III I consider the relationship between truth and existence. In chapter 5, I defend Pluralism about truth: in some domains of discourse, I claim, semantic reference plays a merely instrumental role in explaining truth. In chapter 6, I show that Hume’s Principle, which is committed by the Quinean criterion to the existence of numbers, can be true even though numbers do not exist. In doing so, I appeal to meta-semantic and diachronic considerations. In the conclusion I compare my views on ontology and commitment to Jody Azzouni’s; and in the appendix I suggest how one might pursue diachronic linguistics. (shrink)

Psychology’s emphasis on empirical investigation has long benefited from conceptual developments taking place in its intellectual community, but also from cognate areas in Philosophy. This paper explores the implications for empirical psychology of a recent conceptual proposal advanced within the philosophy of perception by Bence Nanay. In particular, Nanay proposes that “pragmatic representations”, i.e., perceptual representations of the properties of objects necessary for the successful completion of actions, are the rightful target for a success semantics. A success semantics (...) is, roughly speaking, a theory of contents according to which the truth conditions of representations are to be identified with the success conditions of actions guided by the representations. The problem arises for Nanay’s proposal in that the empirical scrutiny of the contents of a pragmatic representation requires that one first ascertains their content, but it is not at all clear whether this could possibly be done given the non-linguistic character of pragmatic representations on the one hand, and the linguistic character of third-personal verbal data acquired through an heterophenomenological methodology on the other. This and other concerns raise worries about the empirical scrutability of Nanay’s proposal. (shrink)