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)

This paper argues in the first place that nominalists (such as Ockham and Buridan) are right in insisting against ontological realists (such as Plato or Scotus) that semantic universality (the property of universally representing symbols as such) 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 (semantic) 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)

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 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)

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)

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)

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)

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)

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)

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)

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)

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.

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)

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 address the problem of the distinction between semantic and conceptual representations from general considerations about how to distinguish a representational kind. I consider three different ways of telling representational kinds apart – in terms of structure, processing and content – and I examine if semantic representations may constitute a distinct kind with respect to each of them. I argue that the best options for semantic representation to be regarded as a distinct representational kind with respect to (...) each of the three criteria conflict with each other, since it appears respectively as an atomic representation, as a sort of procedural rule or as a structured complex. (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)

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)

Artificial intelligence and robots may progressively take a more and more prominent place in our daily environment. Interestingly, in the study of how humans perceive these artificial entities, science has mainly taken an anthropocentric perspective (i.e., how distant from humans are these agents). Considering people’s fears and expectations from robots and artificial intelligence, they tend to be simultaneously afraid and allured to them, much as they would be to the conceptualisations related to the divine entities (e.g., gods). In two experiments, (...) we investigated the proximity of representation between artificial entities (i.e., artificial intelligence and robots), divine entities and natural entities (i.e., humans and other animals) at both an explicit (Study 1) and an implicit level (Study 2). In the first study, participants evaluated these entities explicitly on positive and negative attitudes. Hierarchical clustering analysis showed that participants’ representation of artificial intelligence, robots and divine entities were similar, while the representation of humans tended to be associated with that of animals. In the second study, participants carried out a word/non-word decision task including religious semantic-related words and neutral words after the presentation of a masked prime referring to divine entities, artificial entities and natural entities (or a control prime). Results showed that after divine and artificial entity primes, participants were faster to identify religious words as words compared to neutral words arguing for a semantic activation. We conclude that people make sense of the new entities by relying on already familiar entities and in the case of artificial intelligence and robots, people appear to draw parallels to divine entities. (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)

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)

The semantic fluency task is commonly used as a measure of one’s ability to retrieve semantic concepts. While performance is typically scored by counting the total number of responses, the ordering of responses can be used to estimate how individuals or groups organize semantic concepts within a category. I provide an overview of this methodology, using Alzheimer’s disease as a case study for how the approach can help advance theoretical questions about the nature of semantic representation. However, many open questions (...) surrounding the validity and reliability of this approach remain unresolved. (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)

It is now part and parcel of the official philosophical wisdom that models are essential to the acquisition and organisation of scientific knowledge. It is also generally accepted that most models represent their target systems in one way or another. But what does it mean for a model to represent its target system? I begin by introducing three conundrums that a theory of scientific representation has to come to terms with and then address the question of whether the semantic view (...) of theories, which is the currently most widely accepted account of theories and models, provides us with adequate answers to these questions. After having argued in some detail that it does not, I conclude by pointing out in what direction a tenable account of scientific representation might be sought. (shrink)

This paper argues for a representational semantic conception of scientific theories, which respects the bare claim of any semantic view, namely that theories can be characterised as sets of models. RSC must be sharply distinguished from structural versions that assume a further identity of ‘models’ and ‘structures’, which we reject. The practice-turn in the recent philosophical literature suggests instead that modelling must be understood in a deflationary spirit, in terms of the diverse representational practices in the sciences. These (...) insights are applied to some mathematical models, thus showing that the mathematical sciences are not in principle counterexamples to RSC. (shrink)

Contemporary decision theory places crucial emphasis on a family of mathematical results called representation theorems, which relate criteria for evaluating the available options to axioms pertaining to the decision-maker’s preferences. Various claims have been made concerning the reasons for the importance of these results. The goal of this article is to assess their semantic role: representation theorems are purported to provide definitions of the decision-theoretic concepts involved in the evaluation criteria. In particular, this claim shall be examined from the perspective (...) of philosophical theories of the meaning of theoretical terms. (shrink)

This paper evaluates Stalnaker’s recent attempt to outline a realist interpretation of possible worlds semantics that lacks substantive metaphysical commitments. The limitations of his approach are used to draw some more general lessons about the non-representational artefacts of formal representations. Three key conclusions are drawn. Stalnaker’s account of possible worlds semantics’ non-representational artefacts does not cohere with his modal metaphysics. Invariance-based analyses of non-representational artefacts cannot capture a certain kind of artefact. Stalnaker must treat instrumentally (...) those aspects of possible worlds formalism governing the interaction between quantification and modality, under any analysis whatsoever of non-representational artefacts. (shrink)

Truth conditional semantics is the project of ‘determining a way of assigning truth conditions to sentences based on A) the extension of their constituents and B) their syntactic mode of combination’. This research program has been subject to objections that take the form of underdetermination arguments, an influential instance of which is presented by Travis: … consider the words ‘The leaf is green,’ speaking of a given leaf, and its condition at a given time, used so as to mean (...) what they do mean in English. How many distinct things might be said in words with all that true of them? Many.… Suppose a Japanese maple leaf, turned brown, was painted green for a decoration. In sorting leaves by colour, one might truly call this one green. In describing leaves to help identify their species, it might, for all the paint, be false to call it that. (shrink)

Three-valued logics are standardly used to formalize gappy languages, i.e., interpreted languages in which sentences can be true, false or neither. A three-valued logic that assigns the same truth value to all gappy sentences is, in our view, insufficient to capture important semantic differences between them. In this paper we will argue that there are two different kinds of pathologies that should be treated separately and we defend the usefulness of a four-valued logic to represent adequately these two types of (...) gappy sentences. Our purpose is to begin the formal exploration of the four-valued logics that could be used to represent the phenomena in question and to show that these phenomena are present in natural language, at least according to some semantic theories of natural language. (shrink)

In Knowledge and the Flow of Information, Fred Dretske explains representational content by appealing to natural indication: a mental representation has its content in virtue of being a reliable natural indicator of a particular type of state of the world. His account fails for several reasons, not the least of which is that it cannot account for misrepresentation. Recognizing this, Dretske adds a twist in his more recent work on representational content (sketched in 'Misrepresentation' and elaborated in Explaining (...) Behavior): a mental representation acquires its semantic content when the fact that it naturally indicates some type of state of the world acquires explanatory relevance. This shift in emphasis from natural indication to function (and, so, to behaviour) is intended to address the disjunction problem. Whether or not it succeeds (I argue that it does not), new problems emerge as a direct result of the shift to emphasis on behaviour. First, although Dretske appeals to appropriate response behaviours for particular types of representations, it is not at all clear that such behaviours exist. Second, Dretske's theory cannot account for representations that never figure in the behaviour of the organism of which they are a part. In response to these problems, I suggest two possible routes to recovery: one, an appeal to implicit beliefs (or dispositions); and, two, an appeal to compositionality. Although it seems clear that Dretske must enlist one of these options if he is to formulate a successful causal naturalist theory of representational content, given his theoretical commitments, neither option is readily available to him. (shrink)

In this paper, we study three representations of lattices by means of a set with a binary relation of compatibility in the tradition of Ploščica. The standard representations of complete ortholattices and complete perfect Heyting algebras drop out as special cases of the first representation, while the second covers arbitrary complete lattices, as well as complete lattices equipped with a negation we call a protocomplementation. The third topological representation is a variant of that of Craig, Haviar, and Priestley. We then (...) extend each of the three representations to lattices with a multiplicative unary modality; the representing structures, like so-called graph-based frames, add a second relation of accessibility interacting with compatibility. The three representations generalize possibility semantics for classical modal logics to non-classical modal logics, motivated by a recent application of modal orthologic to natural language semantics. (shrink)

This article proposes a neurobiologically motivated theory of meaning as internal representation that holds on to the principle of compositionality, but negates the principle of semantic constituency. The approach builds on neurobiological findings regarding topologically structured cortical feature maps and the mechanism of object-related binding by neuronal synchronization. It incorporates the Gestalt principles of psychology and is implemented by recurrent neural networks. The semantics to be developed is structurally analogous to some variant of model-theoretical semantics. The semantics (...) to be developed is a neuro-emulative model-theoretical semantics of a first-order language. The model-theoretical semantics is merely denotational and does not imply anything about the structures of the mind or the underlying neural mechanisms that enable producing and comprehend meaningful expressions. The relation between a mental representation and its content is some form of causal-informational covariation. (shrink)

In the context of propositional logics, we apply semantics modulo satisfiability—a restricted semantics which comprehends only valuations that satisfy some specific set of formulas—with the aim to efficiently solve some computational tasks. Three possible such applications are developed.We begin by studying the possibility of implicitly representing rational McNaughton functions in Łukasiewicz Infinitely-valued Logic through semantics modulo satisfiability. We theoretically investigate some approaches to such representation concept, called representation modulo satisfiability, and describe a polynomial algorithm that builds representations (...) in the newly introduced system. An implementation of the algorithm, test results and ways to randomly generate rational McNaughton functions for testing are presented. Moreover, we propose an application of such representations to the formal verification of properties of neural networks by means of the reasoning framework of Łukasiewicz Infinitely-valued Logic.Then, we move to the investigation of the satisfiability of joint probabilistic assignments to formulas of Łukasiewicz Infinitely-valued Logic, which is known to be an NP-complete problem. We provide an exact decision algorithm derived from the combination of linear algebraic methods with semantics modulo satisfiability. Also, we provide an implementation for such algorithm for which the phenomenon of phase transition is empirically detected.Lastly, we study the game theory situation of observable games, which are games that are known to reach a Nash equilibrium, however, an external observer does not know what is the exact profile of actions that occur in a specific instance; thus, such observer assigns subjective probabilities to players actions. We study the decision problem of determining if a set of these probabilistic constraints is coherent by reducing it to the problems of satisfiability of probabilistic assignments to logical formulas both in Classical Propositional Logic and Łukasiewicz Infinitely-valued Logic depending on whether only pure equilibria or also mixed equilibria are allowed. Such reductions rely upon the properties of semantics modulo satisfiability. We provide complexity and algorithmic discussion for the coherence problem and, also, for the problem of computing maximal and minimal probabilistic constraints on actions that preserves coherence.prepared by Sandro Márcio da Silva Preto.E-mail: spreto@ime.usp.brURL:https://doi.org/10.11606/T.45.2021.tde-17062021-163257. (shrink)

All accounts of language acquisition agree that, by around age 4, children’s knowledge of grammatical constructions is abstract, rather than tied solely to individual lexical items. The aim of the present research was to investigate, focusing on the passive, whether children’s and adults’ performance is additionally semantically constrained, varying according to the distance between the semantics of the verb and those of the construction. In a forced‐choice pointing study (Experiment 1), both 4‐ to 6‐year olds (N = 60) and (...) adults (N = 60) showed support for the prediction of this semantic construction prototype account of an interaction such that the observed disadvantage for passives as compared to actives (i.e., fewer correct points/longer reaction time) was greater for experiencer‐theme verbs than for agent‐patient and theme‐experiencer verbs (e.g., Bob was seen/hit/frightened by Wendy). Similarly, in a production/priming study (Experiment 2), both 4‐ to 6‐year olds (N = 60) and adults (N = 60) produced fewer passives for experiencer‐theme verbs than for agent‐patient/theme‐experiencer verbs. We conclude that these findings are difficult to explain under accounts based on the notion of A(rgument) movement or of a monostratal, semantics‐free, level of syntax, and instead necessitate some form of semantic construction prototype account. (shrink)

This study focuses on concepts and, ultimately, their possible implementation in brains. Especially salient is analysis of Jerry Fodor's work. The view of concepts found therein is one where many of both are "simple": to be ascribed or to token most concepts doesn't require being ascribed or tokening any other concepts, and most symbols lack "parts" which are themselves symbols. This is, I think, a very popular, and mistaken, view. ;In chapter 1, I argue that Fodor's theory of content is, (...) contra its goals, neither naturalistic nor atomistic. A deep mistake undermines both, viz. that there's no way to individuate a mental symbol non-semantically. This leads to chapter 2, where I explore the much neglected notion of Mentalese syntax. I argue that there are three possible principles of syntactic type individuation, and that these turn out not only to be incompatible but also inadequate for a "language of thought." I conclude that the idea of simple mental symbols is in trouble. ;This then allows me to argue in chapter 3 that we don't have to fear intentional holism , which sanctions the prevalence of complex concepts. I next sketch, in chapter 4, the sort of complex symbols needed to implement complex concepts. The chapter's bulk consists in an empirical argument for the complexity view via seven domains of current cognitive science, including concept context dependency, typicality effects, association, and reasoning. ;Chapter 5 concludes by exploring connectionism. I argue that, despite problems, connectionism seems on the right track in a way that Fodor's computationalism isn't. For example, it's more explicitly brain-like; in dropping the idea of mental computation over symbols it's free from the syntax problems of chapter 2; and, most important, it's highly compatible with the complexity view, which best characterized the cognitive processes of chapter 4. (shrink)

In this commentary, I propose that horizontal and vertical dimensions of space are represented together inside a common metrics mechanism located in the parietal cortex. Importantly, this network is also involved in the processing of number magnitudes and environment-directed actions. Altogether, the evidence suggests that different magnitude dimensions could be intertwined with the horizontality and verticality of our world representation.

The central concern of this article is whether the semantic approach has the resources to appropriately capture the core tenets of structural realism. Chakravartty (2001) has argued that a realist notion of correspondence cannot be accommodated without introducing a linguistic component, which undermines the approach itself. We suggest that this worry can be addressed by an appropriate understanding of the role of language in this context. The real challenge, however, is how to incorporate the core notion of `explanatory approximate truth' (...) in such a way that the emphasis on structure is retained. (shrink)

Dretske has argued that, unlike the content of beliefs and desires, the contents of innate representations cannot in principle play a role in the causal explanation of an individual's behavior. I examine this "asymmetry" and against it, I argue that the content of innate mental representations too can play a causal role in the explanation of behavior.

In order to resolve problems about the normative aspects of representation without having to (1) provide a naturalized theory of intentional/semantic properties, (2) accept non-natural intentional/semantic properties into our worldview, or (3) eliminate intentionality, this article questions a basic assumption about the metaphysics of representation: that representation involves representation-objects. An alternative, nonreifying approach to the metaphysics of representation is introduced and developed in detail. The argumentative strategy is as follows. First, an adverbial view of linguistic representation is introduced. Two potential (...) objections are identified and considered. To respond to these objections, relationships between physical form and linguistic/representational form are examined. In the process, two ways of idealizing away from the heterogeneous details of actual language use are introduced: idealization toward homogeneity and idealization toward complete heterogeneity. I argue that an adverbial view of linguistic representation both allows for and requires that we idealize toward complete heterogeneity and that doing so has important implications for (1) our understanding of the relationship between physical form and representational form and (2) property attribution in general. These implications provide further indirect support for the alternative metaphysics of representation developed here. (shrink)

Computational modeling and eye-tracking were used to investigate how phonological and semantic information interact to influence the time course of spoken word recognition. We extended our recent models to account for new evidence that competition among phonological neighbors influences activation of semantically related concepts during spoken word recognition . The model made a novel prediction: Semantic input modulates the effect of phonological neighbors on target word processing, producing an approximately inverted-U-shaped pattern with a high phonological density advantage at an intermediate (...) level of semantic input—in contrast to the typical disadvantage for high phonological density words in spoken word recognition. This prediction was confirmed with a new analysis of the Apfelbaum et al. data and in a visual world paradigm experiment with preview duration serving as a manipulation of strength of semantic input. These results are consistent with our previous claim that strongly active neighbors produce net inhibitory effects and weakly active neighbors produce net facilitative effects. (shrink)

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the (...) representations of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

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.

Constructs developed for the semantics of artificial languages are often proposed as the proper description of aspects of the semantics of natural languages. Most of us are familiar with the claims that conjunction, disjunction, negation, and material implication in standard versions of propositional calculus describe the meaning of “and”, “or”, “not”, and “if …, then …” in English. The argument for such claims is not only that these constructs account for meanings in English but that they offer the (...) advantage of well-understood formal apparatus for the explication of meaning in natural language. The argument against such claims is that explications based on this apparatus leave important aspects of the meaning of “and”, “or”, “not”, and “if …, then …” unexplicated. It is charged that the advantage of a well-understood formalism is secured at the expense of truth. Many of the most significant issues in philosophic logic are or depend on questions about whether constructs from artificial languages provide adequate semantic descriptions for natural languages. (shrink)

The Distributional Compositional Categorical model is a mathematical framework that provides compositional semantics for meanings of natural language sentences. It consists of a computational procedure for constructing meanings of sentences, given their grammatical structure in terms of compositional type-logic, and given the empirically derived meanings of their words. For the particular case that the meaning of words is modelled within a distributional vector space model, its experimental predictions, derived from real large scale data, have outperformed other empirically validated methods (...) that could build vectors for a full sentence. This success can be attributed to a conceptually motivated mathematical underpinning, something which the other methods lack, by integrating qualitative compositional type-logic and quantitative modelling of meaning within a category-theoretic mathematical framework. The type-logic used in the DisCoCat model is Lambekʼs pregroup grammar. Pregroup types form a posetal compact closed category, which can be passed, in a functorial manner, on to the compact closed structure of vector spaces, linear maps and tensor product. The diagrammatic versions of the equational reasoning in compact closed categories can be interpreted as the flow of word meanings within sentences. Pregroups simplify Lambekʼs previous type-logic, the Lambek calculus. The latter and its extensions have been extensively used to formalise and reason about various linguistic phenomena. Hence, the apparent reliance of the DisCoCat on pregroups has been seen as a shortcoming. This paper addresses this concern, by pointing out that one may as well realise a functorial passage from the original type-logic of Lambek, a monoidal bi-closed category, to vector spaces, or to any other model of meaning organised within a monoidal bi-closed category. The corresponding string diagram calculus, due to Baez and Stay, now depicts the flow of word meanings, and also reflects the structure of the parse trees of the Lambek calculus. (shrink)

In Sweet Liberty, writer and director Alan Alda dramatizes the process of turning a scholarly study about the American Revolutionary War into a Hollywood film; he does so in ways that bring out the ethical complexities of adaptation, and eventually takes them to a meta-filmic level rarely seen in non-experimental cinema. While Sweet Liberty initially comes off as a light comedy with a predictable plot and ending, on closer inspection it compels us to reflect on the relationship between historical research (...) and the popular entertainment industry. Although Alda appears to chastise the makers of period films who seek to capitalize on “history” without paying heed to historical facts, his professorial hero is not particularly critically minded either. Intentionally or not, Alda demonstrates that evaluating a mainstream history film cannot be reduced to a dichotomy between truth and fiction, and that research-based knowledge should also be viewed with a healthy skepticism. (shrink)

InReference and Consciousness,1John Campbell attempts to a make a case that what he calls ‘the Relational View’ of visual experience, a view that he champions, is superior to what he calls ‘the Representational View’.2I argue that his attempt fails. In section 1, I spell out the two views. In section 2, I outline Campbell's case that the Relational View is superior to the Representational View and offer a diagnosis of where Campbell goes wrong. In section 3, I examine (...) the case in detail and argue that it fails. Finally, in section 4, I mention two very well-known problems for the Relational View that are unresolved in the book. (shrink)

Ontological realism is a philosophical stance that provides a definitional framework for ontologies and is referred to by various applied ontologists. From a computer science perspective, ontologies are often associated with formal languages for the representation of ontologies like the Web Ontology Language (OWL). It has, however, not been made explicit how the realist framework is related to the representation formalism. We analyse how the representational units of OWL can be used for modelling realist ontologies. While OWL is sufficiently (...) close to the realist framework of ontologies to describe them, there are categories in OWL that are alien to realist ontologies or duplicate categories in realist ontologies. This clarification allows separating talk about ontologies in general from talk about their specific representation. (shrink)

The main task of Cognitive Science is to construct concepts and models that would be superordinate to knowledge in the various particular cognitive sciences. In particular, one major objective is to formulate a hypergeneral description of representations that could encompass all descriptions given in subordinate domains.A first basic distinction is between natural and rational representations, i.e. given mental entities and representations that are governed by prescriptive rules coming from logical or scientific thought. In addition, representations must be described in respect (...) to several sources of variability, which are tentatively listed here.Description of natural representations is based on a distinction between taken representations, which are mental events, and type representations, which are lasting structures registered in memory. The connection between them can be modelled through the concept of activation.One advantage of activation models is their large compatibilty, not only with experimental evidence in cognitive psychology, but also with facts and hypotheses in neurosciences, and programming modes or requirements in artificial intelligence. Comprehension of natural language is a highly representative domain in this respect, which exemplifies the power of these concepts. (shrink)