This paper exploits recent work on the normative and constitutive roles of knowledge in practical rationality, to put pressure on the idea that speakers could communicate without exploiting linguisticknowledge. I defend cognitivism about meaning, the view that speakers haverationally accessible(i.e., implicit rather than tacit) knowledge of semantic facts and principles, and that this knowledge is constitutive of their linguistic competence.

Over the last decade, AI models of language and word meaning have been dominated by what we might call a statistics-of-occurrence, strategy: these models are deep neural net structures that have been trained on a large amount of unlabeled text with the aim of producing a model that exploits statistical information about word and phrase co-occurrence in order to generate behavior that is similar to what a human might produce, or representations that can be probed to exhibit behavior similar to (...) what a human might produce (meaningsemblant behavior). Examples of what we can call Statistics-of-Occurrence Models (SOMs) include: Word2Vec (CBOW and Skip-Gram), BERT, GPT-3, and, most recently, ChatGPT. Increasingly, there have been suggestions that such systems have semantic understanding, or at least a proto-version of it. This paper argues against such claims. I argue that a necessary condition for a system to possess semantic understanding is that it function in ways that are causally explainable by appeal to its semantic properties. I then argue that SOMs do not plausibly satisfy this Functioning Criterion. Rather, the best explanation of their meaning-semblant behavior is what I call the Statistical Hypothesis: SOMs do not themselves function to represent or produce meaningful text; they just reflect the semantic information that exists in the aggregate given strong correlations between word placement and meaningful use. I consider and rebut three main responses to the claim that SOMs fail to meet the Functioning Criterion. The result, I hope, is increased clarity about why and how one should make claims about AI systems having semantic understanding. (shrink)

Understanding Semantics offers an up-to-date, broad and thorough introduction to linguistic semantics, the field of linguistic meaning central to the understanding of language. The book takes a step-by-step approach, starting with the basic concepts and moving through central questions to an examination of the methods and results of the science of linguistic meaning.

In his essay ‘“Conceptual Truth”’, Timothy Williamson (2006) argues that there are no truths or entailments that are constitutive of understanding the sentences involved. In this reply I provide several examples of entailment patterns that are intuitively constitutive of understanding in just the way that Williamson rejects, and I argue that Williamson’s argument does nothing to show otherwise. Williamson bolsters his conclusion by appeal to a certain theory about the nature of understanding. I argue that his theory (...) fails to consider the role that the structure of a sentence plays in determining its meaning. The cases I present suggest that this role imposes greater cognitive requirements on understanding than Williamson can acknowledge. (shrink)

In his monograph Semantic Relationism, Kit Fine proposes two characterizations of coordination between proper names: an intuitive test; and a technical definition. The intuitive characterization is grounded in a notion of understanding distinct from the familiar notion of linguistic competence. Three prima facie appealing proposals to characterize this notion of understanding will be examined in the present paper and then dismissed as intrinsically implausible or as incompatible with Fine’s semantics. Not even his technical characterization of coordination, involving (...) the notion of semantic requirement, will enable us to escape the impasse. Ultimately, the question of what exactly coordination between names is will remain open. (shrink)

Most theories of semantic competence in natural language implicitly assume the Language of Thought Hypothesis. According to this hypothesis, all human cognition consists in the deployment of a language of thought. This language of thought is supposed to be independent of natural language, yet at the same time, it is supposed to be semantically isomorphic with natural language. Given this assumption, it is easy to answer basic questions regarding semantic competence in natural language. What are semantic properties (...) of natural language, and how did they originate? Natural language inherits the semantic properties of the language of thought it is used to express. What does semantic competence consist in? It consists in knowing how to translate items in one's language of thought into a public medium. ;The starting point of this dissertation is the rejection, by some prominent paradigms in cognitive science, of the view that human cognition consists in the deployment of a language of thought that is, at the same time, independent of natural language, yet semantically isomorphic with it. The dissertation constitutes a fledgling attempt to explore an alternative approach to explaining semantic competence in natural language, an approach that is compatible with this rejection of the Language of Thought Hypothesis. ;Rather than conceive of natural language as a tool for expressing items in a pre-existing, semantically isomorphic, language of thought, I urge that language be conceived of as a norm-governed social practice. On this view, the semantic properties of natural language are determined by the inferential norms governing linguistic performances. In order to explain the origin of its semantic properties, one must explain the origin of the inferential norms that govern language. In order to explain what semantic competence consists in, one must explain how individuals learn to abide by these inferential norms. The bulk of the dissertation is devoted to showing that neither of these explanatory projects requires endorsing the Language of Thought Hypothesis. I do this by sketching the form that such explanations might take, and showing that they are consistent with much current research in ethology, comparative psychology, developmental psychology, and evolutionary biology. (shrink)

Elizabeth Fricker; IV*—Semantic Structure and Speakers' Understanding1, Proceedings of the Aristotelian Society, Volume 83, Issue 1, 1 June 1983, Pages 49–66, h.

Hans-Georg Gadamer argues that language is the medium of all understanding and thus that it is the medium through which we can reach understanding with one another. Yet many today are sceptical of this claim and worry that Gadamerian hermeneutics ignores at its own peril the limits of the particular discourses that people utilize to reach understanding with one another. I argue here that this criticism rests on the assumption that, for Gadamer, it is the semantic (...) features of a language alone that allow it to function as the medium for shared understanding. I argue that focusing solely on semantic agreement as the source of understanding ignores the role that mutual recognition plays in allowing language to serve as a medium for shared understanding. I turn to discussions in several of Gadamer’s later essays to examine how he conceives of the mutual recognition that is essential for communicative understanding. (shrink)

People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as well as individual and age differences in cognitive performance. We conclude that the extent to which experience-dependent changes in semantic representations contribute to individual differences in cognitive aging (...) remains unclear. To help fill this gap, we outline an empirical agenda that utilizes network analysis and involves the concurrent assessment of large-scale semantic networks and cognitive performance in younger and older adults. We present preliminary data to establish the feasibility and limitations of such empirical, network-analytical approaches. (shrink)

This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are discussed, and (...) a prototype natural-language-understanding system is presented as an illustration. (shrink)

The book series Linguistische Arbeiten (LA) publishes high-quality work in linguistics that addresses current issues in synchrony and diachrony, theoretically or empirically oriented.

John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? (...) Yes: Everything makes sense. The question is: What sense does it make?" This essay explores what sense it makes to say that syntax by itself is sufficient for semantics. (shrink)

This essay is part of a larger project aimed at making sense of rational thought and agency as part of the natural world. It provides a semantic framework for thinking about the contents of: 1) descriptive thoughts and sentences having a representational or mind-to-world direction of fit, and which manifest our capacity for theoretical rationality; and 2) prescriptive and intentional sentences having an expressive or world-to-mind direction of fit, and which manifest our capacity for practical rationality. I use a (...) modified version of Allan Gibbard’s hyperstate semantics, employing both maximally determinate possible worlds and maximally determinate plans of action, as a basis for providing a unified understanding of moral judgments and expressions of individual and collective intentionality – they one and all give voice to our ability as rational agents to adopt the perspectives of various individuals within a community and consider how we would behave were we in their positions. In the course of spelling out the view I draw on and criticize ideas that Wilfrid Sellars advanced in the middle of the 20th century, while employing the tools of contemporary modal logic and model-theoretic semantics to give perspicuous formulation to his thought that the moral judgment ‘one ought to do A’ should be understood in terms of the collective intention ‘we shall do A’, where the pronoun denotes the unrestricted class of rational agents and the ‘ought’ is in some sense unconditionally binding. (shrink)

In this research, Description Logics (DLs) will be employed for logical description, logical characterisation, logical modelling and ontological description of concept understanding in terminological systems. It’s strongly believed that using a formal descriptive logic could support us in revealing logical assumptions whose discovery may lead us to a better understanding of ‘concept understanding’. The Structure of Observed Learning Outcomes (SOLO) model as an appropriate model of increasing complexity of humans’ understanding has supported the formal analysis.

I explore a strand of reception history that follows Rudolf Carnap’s shift from a purely syntactical analysis of constructed languages to his conception of pure semantics. My exploration focuses on Gustav Bergmann’s and Everett Hall’s interpretation of pure semantics, their understanding of what constitutes a ’formal’ investigation of language, and their arguments concerning the relationship between expressions and their extra-linguistic referents. I argue that Bergmann and Hall strongly misread Carnap’s semantic project and, subsequently, their misunderstanding is passed down (...) through colleagues and students. (shrink)

Presented in this book is a theory of concept formation and understanding that does not make use of a notion of an innate mental language as a means of concept representation. Instead, experimental concepts are treated semantically as stabilising structuring of growing sets of data, which are sets of experienced satisfaction situations for expressions, and theoretical concepts are based on coherent sets of general sentences held true. There are two kinds of structures to be established: general concepts by means (...) of similarity sets under perspectives and historical concepts. This gives rise to a theory of understanding new situations and expressions by integrating new data into established sets of data salva stability, or by extending the conceptual structure in a metaphorical or metonymical way. The theory provides a way to understand what identity between propositional attitudes amounts to, especially how people can have more or less the same belief. (shrink)

Kit Fine (2007) outlines an account of semantic coordination, an account motivated by the role of semantic coordination in cognition. Actually, Fine outlines two accounts of semantic coordination, one in terms of co-reference and another in terms of synonymy. I argue, first, that Fine's two accounts are not equivalent, with one being logically stronger than the other, but second and more importantly, that neither account is correct. I outline an alternative account of semantic coordination – the (...) epistemic conception of semantic coordination – that links semantic and epistemic aspects of cognition more directly. The most surprising result of my alternative account of semantic coordination is that semantic coordination is a relation that can hold between elements of thought and language of different semantic types. I close the paper by briefly outlining some applications of the idea that semantic coordination is a relation that can hold across semantic types. (shrink)

This article aims to demonstrate the interdependence of semantics and noetics against the referentialist trend in Abelard studies conceiving semantics as confined to the truth/falsity function. The article takes as a turning point of the argument Abelard’s question “can a true proposition generate a false understanding?” which secondary literature does not take into account. Starting from the analysis of this question, the article aims to show the development of an enhanced notion of understanding compared to the Boethian one. (...) The core of this enhanced notion of understanding is the action of attentio, which is the condition for the elaboration of a coherent and global definition of signification. The analysis of the mental action of attentio entails the description of other kinds of mental actions, leading one to conceive understanding as a multi-layered complex of actions. (shrink)

Increasing computational power and improving deep learning methods have made computer vision technologies pervasively common in urban environments. Their applications in policing, traffic management, and documenting public spaces are increasingly common (Ridgeway 2018, Coifman et al. 1998, Sun et al. 2020). Despite the often-discussed biases in the algorithms' training and unequally borne benefits (Khosla et al. 2012), almost all applications similarly reduce urban experiences to simplistic, reductive, and mechanistic measures. There is a lack of context, depth, and specificity in these (...) practices that enables semantic knowledge or analysis within urban contexts, especially within the context of using and occupying urban space. This paper will critique existing uses of artificial intelligence and computer vision in urban practices to propose a new framework for understanding people, action, and public space. This paper revisits Geertz's (1973) use of thick descriptions in generating interpretive theories of culture and activity and uses this lens to establish a framework to approach evaluating the varied uses of computer vision technologies that weigh meaning. By discussing cases of implemented examples of urban computer vision—from LinkNYC and Numina's urban measurements to the Detroit Police's use of DataWorks Plus's facial recognition technology—it proposes a framework for evaluating the thickness of the algorithm's conclusions against the computational method's complexity required to produce that outcome. Further, we discuss how the framework's positioning may differ (and conflict) between different users of the technology, from engineer to urban planner and policymaker, to citizen. This paper also discusses how the current use and training of deep learning algorithms and how this process limits semantic learning and proposes three potential methodologies toward gaining a more contextually specific, urban-semantic, description of urban space relevant to urbanists. This paper contributes to the critical conversations regarding the proliferation of artificial intelligence by challenging the current applications of these technologies in the urban environment by highlighting their failures within this context while also proposing an evolution of these algorithms that may ultimately make them sensitive and useful within this spatial and cultural milieu. (shrink)

Hans-Georg Gadamer argues that language is the medium of all understanding and thus that it is the medium through which we can reach understanding with one another. Yet many today are sceptical of this claim and worry that Gadamerian hermeneutics ignores at its own peril the limits of the particular discourses that people utilize to reach understanding with one another. I argue here that this criticism rests on the assumption that, for Gadamer, it is the semantic (...) features of a language alone that allow it to function as the medium for shared understanding. I argue that focusing solely on semantic agreement as the source of understanding ignores the role that mutual recognition plays in allowing language to serve as a medium for shared understanding. I turn to discussions in several of Gadamer’s later essays to examine how he conceives of the mutual recognition that is essential for communicative understanding. (shrink)

Semantic externalism is the view that the meanings of referring terms, and the contents of beliefs that are expressed by those terms, are not fully determined by factors internal to the speaker but are instead bound up with the environment. The debate about semantic externalism is one of the most important but difficult topics in philosophy of mind and language, and has consequences for our understanding of the role of social institutions and the physical environment in constituting (...) language and the mind. In this long-needed book, Jesper Kallestrup provides an invaluable map of the problem. Beginning with a thorough introduction to the theories of descriptivism and referentialism and the work of Frege and Kripke, Kallestrup moves on to analyse Putnam’s Twin Earth argument, Burge’s arthritis argument and Davidson’s Swampman argument. He also discusses how semantic externalism is at the heart of important topics such as indexical thoughts, epistemological skepticism, self-knowledge, and mental causation. Including chapter summaries, a glossary of terms, and an annotated guide to further reading, _Semantic Externalism_ an ideal guide for students studying philosophy of language and philosophy of mind. (shrink)

I advocate a theory of syntactic semantics as a way of understanding how computers can think (and how the Chinese-Room-Argument objection to the Turing Test can be overcome): (1) Semantics, considered as the study of relations between symbols and meanings, can be turned into syntax – a study of relations among symbols (including meanings) – and hence syntax (i.e., symbol manipulation) can suffice for the semantical enterprise (contra Searle). (2) Semantics, considered as the process of understanding one domain (...) (by modeling it) in terms of another, can be viewed recursively: The base case of semantic understanding –understanding a domain in terms of itself – is syntactic understanding. (3) An internal (or narrow ), first-person point of view makes an external (or wide ), third-person point of view otiose for purposes of understanding cognition. (shrink)

This meta-study of animal semantics is anchored in two claims, seemingly creating a fuzzy mismatch, that animal utterances generally appear to be simple in structure and content variation and that animals’ communicative understanding seems disproportionally more advanced. A set of excerpted, new studies is chosen as basis to discuss whether the semantics of animal uttering and understanding can be fused into one. Studies are prioritised due to their relatively complex designs, giving priority to dynamics between syntax, semantics, pragmatics, (...) and between utterers and receivers in context. A communicational framework based on utterance theory is applied as a lens for inspection of how these aspects relate to the assumed mismatch. Inspection and discussions of the studies bring several features to surface of which five are stressed in the following. Firstly, both syntactic structures and possible semantic content are seen as lean, although richer than earlier believed, and research continues to reveal new complexities in utterances. Secondly, there is a clear willingness to broaden the perception of animals’ semantic capacity to comprehend communication both by arguing theoretically and by generating empirical research in new contexts. Thirdly, the ambition to make sense of these tendencies is still often motivated by an evolutionary search for early building blocks for verbal language, with the pro et cons that such a position can have. Fourthly, the ‘allowed’ scientific frame for studying semantic capacity among animals is extended to new fields and contexts challenging the only-in-the-wild norm. Fifthly, the dilemma of integrating uttering and understanding as aspects of an after all functional communicational system, calls for new epistemological concepts to make sense of the claimed mismatch. Affordances, abduction, life-genre, and lifeworld are suggested. (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)

Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge (...) methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts. (shrink)

The article argues that cognitive linguistic theory may prove an alternative to the Montague paradigm for designing natural language understanding systems. Within this framework it describes a system which models language understanding as a dialogical process between user and computer. The system operates with natural language texts as input and represent language meaning as entity-relationship diagrams.

I examine one of the conceptual cornerstones of the field known as computational neuroscience, especially as articulated in Churchland et al. (1990), an article that is arguably the locus classicus of this term and its meaning. The authors of that article try, but I claim ultimately fail, to mark off the enterprise of computational neuroscience as an interdisciplinary approach to understanding the cognitive, information-processing functions of the brain. The failure is a result of the fact that the authors provide (...) no principled means to distinguish the study of neural systems as genuinely computational/information-processing from the study of any complex causal process. I then argue for two things. First, that in order to appropriately mark off computational neuroscience, one must be able to assign a semantics to the states over which an attempt to provide a computational explanation is made. Second, I show that neither of the two most popular ways of trying to effect such content assignation -- informational semantics and 'biosemantics' -- can make the required distinction, at least not in a way that a computational neuroscientist should be happy about. The moral of the story as I take it is not a negative one to the effect that computational neuroscience is in principle incapable of doing what it wants to do. Rather, it is to point out some work that remains to be done. (shrink)

Minimal semantics is sometimes characterised as a ‘neo-Gricean’ approach to meaning. This label seems reasonable since a key claim of minimal semantics is that the minimal contents possessed by sentences (akin to Grice’s technical notion of ‘what is said by a sentence’) need not be (and usually are not) what is communicated by a speaker who utters those sentences. However, given an affinity between the two approaches, we might expect that a well-known challenge for the Gricean – namely that their (...) account fails to fit with the psychological evidence concerning linguistic understanding – could also be levelled at the minimalist, and indeed this seems to be the basis of Recanati’s challenge to minimalism from his ‘availability principle’ (Recanati 2004). This paper aims to explore the relationship between semantics and psychology and show how both Gricean and minimalist approaches can avoid the challenge from psychological evidence. I conclude by suggesting that the way in which minimalism avoids this challenge also helps the account to defuse Clapp’s ‘naturalistic objection’ (Clapp 2007) that there are no grounds for selecting a correct minimal semantic theory. (shrink)

Minimal semantics is sometimes characterised as a ‘neo-Gricean’ approach to meaning. This label seems reasonable since a key claim of minimal semantics is that the minimal contents possessed by sentences (akin to Grice’s technical notion of ‘what is said by a sentence’) need not be (and usually are not) what is communicated by a speaker who utters those sentences. However, given an affinity between the two approaches, we might expect that a well-known challenge for the Gricean – namely that their (...) account fails to fit with the psychological evidence concerning linguistic understanding – could also be levelled at the minimalist, and indeed this seems to be the basis of Recanati’s challenge to minimalism from his ‘availability principle’ (Recanati 2004). This paper aims to explore the relationship between semantics and psychology and show how both Gricean and minimalist approaches can avoid the challenge from psychological evidence. I conclude by suggesting that the way in which minimalism avoids this challenge also helps the account to defuse Clapp’s ‘naturalistic objection’ (Clapp 2007) that there are no grounds for selecting a correct minimal semantic theory. (shrink)

Holistic theories of meaning have, at least since Dummett’s Frege: The Philosophy of language, been assumed to be problematic from the perspective of the incremental nature of natural language learning. In this essay I argue that the general relationship between holism and language learning is in fact the opposite of that claimed by Dummett. It is only given a particular form of language learning, and a particular form of holism, that there is a problem at all; in general, for all (...) forms of holism, and irrespective of how language learning is understood, semantic holism is conducive to language learning. The paper has three main parts. In the first, I demonstrate with the use of a simple formal system, that the form of holism that generates the problem that Dummett draws attention to is really decomposable into three distinct components, each of which is necessary for the problem to arise. In the second part, I demonstrate that even Dummett’s strong form of holism is compatible with one natural way in which to understand the incremental nature of language learning. In the third part, I outline the reasons why all forms of holism are conducive to language learning and offer two ways in which this general fact can be spelled out precisely. I end the paper by addressing some possible objections, and in doing so I draw attention to some affinities between semantic holism and the principle of compositionality, a semantic principle which has long been assumed to be conducive to language learning. (shrink)

In this paper a logical interpretation of semantic nets and graph grammars is proposed for modelling natural language understanding and creating language understanding computer systems. An example of parsing a Finnish question by graph grammars and inferring the answer to it by a semantic net representation is provided.

Lexical Semantics for Terminology: An introduction explores the interconnections between lexical semantics and terminology. More specifically, it shows how principles borrowed from lexico-semantic frameworks and methodologies derived from them can help understand terms and describe them in resources. It also explains how lexical analysis complements perspectives entirely focused on knowledge. Issues such as term identification, meaning, polysemy, relations between terms, and equivalence are discussed thoroughly and illustrated with various examples taken from different fields of knowledge. This book is intended (...) for readers who are interested in words and need to handle specialized terms as part of their activities, i.e. terminologists, translators, lexicographers, corpus linguists. A background in terminology or lexical semantics is not required since all notions are defined and explained. This book should complement other textbooks on terminology that do not focus on lexical semantics per se. (shrink)

Semantic Leaps explores how people combine knowledge from different domains in order to understand and express new ideas. Concentrating on dynamic aspects of on-line meaning construction, Coulson identifies two related sets of processes: frame-shifting and conceptual blending. Frame-shifting is semantic reanalysis in which existing elements in the contextual representation are reorganized into a new frame. Conceptual blending is a set of cognitive operations for combining partial cognitive models. By addressing linguistic phenomena often ignored in traditional meaning research, Coulson (...) explains how processes of cross-domain mapping, frame-shifting, and conceptual blending enhance the explanatory adequacy of traditional frame-based systems for natural language processing. The focus is on how the constructive processes speakers use to assemble, link, and adapt simple cognitive models underlie a broad range of productive language behavior. (shrink)

Evaluating the usefulness of Davidson's semantics to computational understanding of language requires an examination of the role of a theory of truth in characterizing sentence meaning and logical form, and in particular of the connection between meaning and belief. The suggested conclusion is that the relevance of Davidson's semantics for computational semantics lies not so much in its methods and particular proposals of logical form as in its general orientation towards "desubstantializing" meaning.

The book is about logical analysis of natural language. Since we humans communicate by means of natural language, we need a tool that helps us to understand in a precise manner how the logical and formal mechanisms of natural language work. Moreover, in the age of computers, we need to communicate both with and through computers as well. Transparent Intensional Logic is a tool that is helpful in making our communication and reasoning smooth and precise. It deals with all kinds (...) of linguistic context in a fully compositional and anti-contextual way. (shrink)