In this paper we propose a way to deal with natural language inference by implementing Modern Type Theoretical Semantics in the proof assistant Coq. The paper is a first attempt to deal with NLI and natural language reasoning in general by using the proof assistant technology. Valid NLIs are treated as theorems and as such the adequacy of our account is tested by trying to prove them. We use Luo’s Modern Type Theory with coercive subtyping as the formal (...) language into which we translate natural language semantics, and we further implement these semantics in the Coq proof assistant. It is shown that the use of a MTT with an adequate subtyping mechanism can give us a number of promising results as regards NLI. Specifically, it is shown that a number of inference cases, i.e. quantifiers, adjectives, conjoined noun phrases and temporal reference among other things can be successfully dealt with. It is then shown, that even though Coq is an interactive and not an automated theorem prover, automation of all of the test examples is possible by introducing user-defined automated tactics. Lastly, the paper offers a number of innovative approaches to NL phenomena like adjectives, collective predication, comparatives and factive verbs among other things, contributing in this respect to the theoretical study of formal semantics using MTTs. (shrink)

We describe a knowledge representation and inference formalism, based on an intensional propositional semantic network, in which variables are structures terms consisting of quantifier, type, and other information. This has three important consequences for natural language processing. First, this leads to an extended, more natural formalism whose use and representations are consistent with the use of variables in natural language in two ways: the structure of representations mirrors the structure of the language and allows re-use phenomena such (...) as pronouns and ellipsis. Second, the formalism allows the specification of description subsumption as a partial ordering on related concepts (variable nodes in a semantic network) that relates more general concepts to more specific instances of that concept, as is done in language. Finally, this structured variable representation simplifies the resolution of some representational difficulties with certain classes of natural language sentences, namely, donkey sentences and sentences involving branching quantifiers. The implementation of this formalism is called ANALOG (A NAtural LOGIC) and its utility for natural language processing tasks is illustrated. (shrink)

This light piece reflects on analogies between two often disjoint streams of research: the logical semantics and pragmatics of natural language and dynamic logics of general information-driven agency. The two areas show significant overlap in themes and tools, and yet, the focus seems subtly different in each, defying a simple comparison. We discuss some unusual questions that emerge when the two are put side by side, without any pretense at covering the whole literature or at reaching definitive conclusions.

Recent work in natural language semantics leads to some new observations on generalized quantifiers. In § 1 we show that English quantifiers of type $ $ are booleanly generated by their generalized universal and generalized existential members. These two classes also constitute the sortally reducible members of this type. Section 2 presents our main result--the Generalized Prefix Theorem (GPT). This theorem characterizes the conditions under which formulas of the form Q1x 1⋯ Qnx nRx 1⋯ xn and q1x 1⋯ qnx (...) nRx 1⋯ xn are logically equivalent for arbitrary generalized quantifiers Qi, qi. GPT generalizes, perhaps in an unexpectedly strong form, the Linear Prefix Theorem (appropriately modified) of Keisler & Walkoe (1973). (shrink)

The topic of temporal meaning in texts has received considerable attention in recent years from scholars in linguistics, logical semantics, cognitive science, and artificial intelligence. Representing Time in Natural Language offers a systematic and detailed account of how we use temporal information contained in a text or in discourse to reason about the flow of time, inferring the order in which events happened when this is not explicitly stated. A new representational system is designed to formalize an appropriately context-dependent (...) notion of situated inference. The Dynamic Aspect Tree, representing temporal dependencies, constitutes a novel and important dynamic temporal logic, one that makes it easy to see "what follows when" from the information given in an ordinary English text. (shrink)

This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according to generative PCFG models. In contrast, we employ a simpler probabilistic model over trees based directly on constituent identity and linear context, and use an EM-like iterative procedure to induce structure. This method produces much higher quality analyses, giving the best published results on the ATIS dataset.

The aim of natural language ontology is to uncover the ontological categories and structures that are implicit in the use of natural language, that is, that a speaker accepts when using a language. This article aims to clarify what exactly the subject matter of natural language ontology is, what sorts of linguistic data it should take into account, how natural language ontology relates to other branches of metaphysics, in what ways natural language ontology is important, (...) and what may be distinctive of the ontological categories and structures reflected in natural language. (shrink)

The study tested how the use of positive- (e.g. beautiful) and negative-valenced (e.g. horrible) words in natural language and its change in time affects the severity of depression and anxiety symptoms among depressed and non-depressed individuals. This longitudinal mixed methods study (N = 40 participants, n = 1440 narratives) with three measurements within a year showed that at the between-person level the use of negative-valenced words was strongly associated with the increase in anxiety and depression symptoms over time while (...) the use of positive-valenced words was slightly associated with the decrease in anxiety and depression symptom. These effects were not supported for within-person level (i.e. changes in word usage). No significant differences were observed in the effects between depressed and non-depressed groups. Summing up, the overall use of positive- and negative-valenced words (particularly negative-valenced words) had a stronger effect on the severity of psychopathological symptoms than their change over time. The results were discussed in the context of natural language processing and its application in diagnosing depression and anxiety symptoms. (shrink)

Hauser defends the proposition that our languages of thought are public languages. One group of arguments points to the coincidence of clearly productive (novel, unbounded) cognitive competence with overt possession of recursive symbol systems. Another group relies on phenomenological experience. A third group cites practical and methodological considerations: Occam's razor and the "streetlight principle" (other things being equal, look under the lamp) that motivate looking for instantiations of outer languages in thought first.

In this paper I review the Neo-Davidsonian semantics of prepositional phrases and secondary predication. I argue that certain types of examples pose challenge to this semantics. I present an alternative to the Neo-Davidsonian analysis which successfully deals with the problematic examples. The core idea lies in representing theta-roles not as functions from events to their participants, but rather as argument-labels encoding the role of each argument in a given verb. As a result, natural-language predicates can now be treated in (...) the manner in which relations are treated in the relational model of data, that is, as naming sets of tuples in which every object is given together with its role named by a corresponding attribute (a theta-role). Such a representation allows the employment of relational algebra operators to calculate the extensions of complex predicates (predicates built out of atomic predicates and/or atomic predicates and prepositions). I lay out the foundations of a relational FOL appropriate for the representation of natural-language predicates and present solutions to the problematic examples. From a practical perspective, the expressions of a relational FOL can be translated to a relational algebra or SQL, which makes it possible to operate with these three languages on the same relational model of data. From a philosophical perspective, a relational FOL permits a return to ‘property-based’ semantics, one in which properties named by predicates are those of individuals, and not of events. (shrink)

This textbook, which is completely self-contained and can be read by anyone with a secondary school education, is the result of the author's material prepared over the past 15 years of teaching introductory natural language semantics to graduate and undergraduate students at McGill University. The intended audience comprises undergraduate and graduate students in linguistics as well as those in philosophy, computer science and psychology with an interest in natural language semantics. The aim of the textbook is to teach (...) the fundamentals of natural language semantics, with English as the principal, though not the exclusive, target language. The principal aim of the textbook is to provide the student with all the basics necessary to be able him or her read research in natural language semantics, regardless of the theory assumed by the author of the research. In contrast to other textbooks in the field, which aim to introduce students to a particular theory of natural language semantics, this textbook seeks to give to its reader a clear overview of the kind of natural language phenomena which, at least prima facie, fall within the ambit of an investigation of natural language semantics; to assist the reader in developing a mastery of the mathematical tools used to formulate hypotheses about the natural language phenomena studied; and to impart to the reader an appreciation of the interplay between hypothesis and data. As a result, the textbook is rich in its presentation of the patterns of English, drawing extensively on the best and most contemporary descriptive grammars of English. The textbook also has more than 500 exercises, with answers to half of them. (shrink)

From a leading authority in artificial intelligence, this book delivers a synthesis of the major modern techniques and the most current research in natural language processing. The approach is unique in its coverage of semantic interpretation and discourse alongside the foundational material in syntactic processing.

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics (...) and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice’s contributions to pragmatics or in interpretation by abduction. (shrink)

Good communication is vital in healthcare both among healthcare professionals and be tween healthcare professionals and their patients And well written documents describing and or explaining the information in structured databases may be easier to comprehend more edifying and even more convincing than the structured data even when presented in tabu lar or graphic form Documents may be automatically generated from structured data using techniques from the eld of natural language generation These techniques are concerned with how the content (...) organisation and language used in a document can be dynamically selected depending on the audience and context They have been used to generate health education ma terials explanations and critiques in decision support systems and medical reports and progress notes.. (shrink)

The question whether natural language can be captured in a formal system has been argued at length, and both a positive and a negative answer has been defended. The paper investigates the main lines of argument for both, and argues that the stalemate that appears to have been reached is an indication that the question itself rests on a wrong conception of the relation between natural languages and formal languages, and hence of the methodological status of (...) formal modelling of natural language. (shrink)

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design—such as “minimal search” criteria from theoretical (...) syntax—adhere to the FEP. This affords a greater degree of explanatory power to the FEP—with respect to higher language functions—and offers linguistics a grounding in first principles with respect to computability. While we mostly focus on building new principled conceptual relations between syntax and the FEP, we also show through a sample of preliminary examples how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel–Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing–Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference. (shrink)

Many people have argued that the evolution of the human language faculty cannot be explained by Darwinian natural selection. Chomsky and Gould have suggested that language may have evolved as the by-product of selection for other abilities or as a consequence of as-yet unknown laws of growth and form. Others have argued that a biological specialization for grammar is incompatible with every tenet of Darwinian theory – that it shows no genetic variation, could not exist in any intermediate forms, (...) confers no selective advantage, and would require more evolutionary time and genomic space than is available. We examine these arguments and show that they depend on inaccurate assumptions about biology or language or both. Evolutionary theory offers clear criteria for when a trait should be attributed to natural selection: complex design for some function, and the absence of alternative processes capable of explaining such complexity. Human language meets these criteria: Grammar is a complex mechanism tailored to the transmission of propositional structures through a serial interface. Autonomous and arbitrary grammatical phenomena have been offered as counterexamples to the position that language is an adaptation, but this reasoning is unsound: Communication protocols depend on arbitrary conventions that are adaptive as long as they are shared. Consequently, language acquisition in the child should systematically differ from language evolution in the species, and attempts to analogize them are misleading. Reviewing other arguments and data, we conclude that there is every reason to believe that a specialization for grammar evolved by a conventional neo-Darwinian process. (shrink)

This chapter outlines a new argument for the view that language has a cognitive role. I suggest that humans exhibit two distinct kinds of belief state, one passively formed, the other actively formed. I argue that actively formed beliefs (_virtual beliefs_, as I call them) can be identified with _premising policies_, and that forming them typically involves certain linguistic operations. I conclude that natural language has at least a limited cognitive role in the formation and manipulation of virtual beliefs.

Despite the fact that natural language has always been one of the most important resources for the study of ontology, many authors continue to regard it as a deceptive guide to the inquiry into what there is. The notion of natural language as a trap is carried over into contemporary metaontological studies, which typically reject natural language as ontologically committing. From a deflationary perspective, this paper aims to argue that ontological commitment occurs in natural languages, (...) with implications for the linguistic relativity hypothesis. To this end, a view based on naturalized epistemology and other aspects of Quine’s philosophy is presented. The perspective of Natural Language Ontology proposed by Moltmann is also introduced, with the goal of offering a new approach that allows a specific analysis of the ontological commitments of natural languages. While Moltmann herself indicates some motivations for this, its potential attractiveness for the study of linguistic relativity will be emphasized here. Finally, it will be suggested that there may be a linguistic bias around the proposed criteria of ontological commitment. (shrink)

In the first part of this article, we show that, contrary to the Gricean tradition, inter-clausal and is not semantically equivalent to logical conjunction and, contrary to temporal approaches such as Bar-Levand Palacas 1980, it is not temporallyloaded. We then explore a commonsenseidea – namely that while sentence juxtaposition might be interpreted either as discourse coordination or subordination, and indicates coordination. SDRT already includes notions of coordinating and subordinating discourse relations (cf. Lascarides and Asher 1993, Asher 1993), and the meaning (...) of and is related to this distinction. Similar distinctions that play a crucial role in anaphora resolution have also appeared in AI – cf. Scha and Polanyi 1988, or Webber 1991. However, this discourse-structure-based distinction has not been well defined yet, and our approach provides independent motivation for it. This paper argues that the semantics of and includes a notion of coordination expressed as the requirement of a Coordinated Discourse Topic (CDT).CDT characterizes aclass of discourse relations, among which are Narration and Result.Once the basic semanticcontribution of and is isolated, effects related to its presence such as changes in temporal structure, blocking of a Discourse Relation, or conditional meanings are shown to follow from the defeasiblearchitecture set up by SDRT. (shrink)

This paper explores two important ways in which the practice of close reading differs from the technique of natural language processing, the use of computer programming to decode, process, and replicate messages within a human language. It does so in order to highlight distinctive features of close reading that are not replicated by natural language processing. The first point of distinction concerns the nature of the meaning generated in each case. While natural language processing proceeds on the (...) principle that a text’s meaning can be deciphered by applying the rules governing the language in which the text is written, close reading is premised on the idea that this meaning lies in the interplay that the text prompts within readers. While the semantic theory of meaning upon which natural language processing programs are based is often taken for granted today, I draw from phenomenological and hermeneutic theories, particularly Wolfgang Iser and Hans-Georg Gadamer, to explain why a different theory of meaning is necessary for understanding the meaning generated by close reading. Second, while natural language processing programs are considered successful when they generate what epistemologists call true beliefs about a text, I argue that close reading aims first and foremost at the development, not of true belief, but of understanding. To develop this distinction, I draw from recent scholarship on the epistemology of education, including work by Duncan Pritchard, to explain how understanding differs from true belief and why attainment of the latter is less educationally significant than the former. (shrink)

This paper gives a characterization of the ontology implicit in natural language and the entities it involves, situates natural language ontology within metaphysics, and responds to Chomskys' dismissal of externalist semantics.

I revisit my earlier arguments for the (trivial) inconsistency of natural languages, and take up the objection that no such argument can be established on the basis of surface usage. I respond with the evidential centrality of surface usage: the ways it can and can't be undercut by linguistic science. Then some important ramifications of having an inconsistent natural language are explored: (1) the temptation to engage in illegitimate reductio reasoning, (2) the breakdown of the knowledge idiom (...) (because its facticity isn't comfortable with every sentence being true and false). Restoring the utility of the knowledge idiom motivates regimentation - the consistentist reinterpretation of natural language inferences (as they occur in real time). It's then sketched how to give the semantics of a natural language despite its inconsistency: Necessary and sufficient truth conditions are dropped in favor of necessary truth conditions and sufficient truth conditions. (shrink)

COVID-19 is a disease that affects the quality of life in all aspects. However, the government policy applied in 2020 impacted the lifestyle of the whole world. In this sense, the study of sentiments of people in different countries is a very important task to face future challenges related to lockdown caused by a virus. To contribute to this objective, we have proposed a natural language processing model with the aim to detect positive and negative feelings in open-text answers (...) obtained from a survey in pandemic times. We have proposed a distilBERT transformer model to carry out this task. We have used three approaches to perform a comparison, obtaining for our best model the following average metrics: Accuracy: 0.823, Precision: 0.826, Recall: 0.793 and F1 Score: 0.803. (shrink)

The fifth chapter provides a detailed discussion of Buridan’s strategy of identifying the conceptual structures discussed in the chapter 4 by means of the various “syntactical clues” provided by spoken and written natural languages. The chapter compares the Buridanian strategy of “regimentation” with the modern strategy of formalization, and argues that for the purposes of a “natural logic” the former is not inferior to the latter. But in order to bridge the conceptual gap between the two approaches, (...) the chapter also discusses a simple extension of standard quantification theory that is capable of faithfully representing a large part of Buridan’s logic. Indeed, the chapter argues that the resulting formal system is in accord not only with Buridan’s logic, but with our natural language intuitions in general, providing more faithful representation of natural language reasoning than standard quantification theory. (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.

Modern weaponry is often too complex for unaided human operation, and is largely or totally controlled by computers. But modern software, particularly artificial intelligence software, exhibits such complexity and inscrutability that there are grave dangers associated with its use in non-benign applications. Recent efforts to make computer systems more accessible to military personnel through natural language processing systems, as proposed in the Strategic Computing Initiative of the Defense Advanced Research Projects Agency, increases rather than decreases the dangers of unpredictable (...) behavior. Defense systems constitute, in fact, a paradigm case of the wrong kind of application for this technology. This cannot be expected to change, since the unpredictability stems from inherent properties of computer systems and of natural languages. (shrink)

A volume of studies in natural language semantics which brings together work by philosophers, logicians and linguists. The main topics treated are: quantification and reference in natural language; the relations between formal logic, programming languages and natural language; pragmatics and discourse meaning; surface syntax and logical meaning. The volume derives from a colloquium organised in 1973 by the Kings College Research Centre, Cambridge and the papers have been edited for publication by Professor Keenan. It is hoped (...) that the collection will make available some of the best work in this fast-moving field and will stimulate further progress by juxtaposing the different approaches and interests represented here. (shrink)

Strawson described ‘descriptive metaphysics’, Bach described ‘natural language metaphysics’, Sapir and Whorf describe, well, Sapir-Whorfianism. And there are other views concerning the relation between correct semantic analysis of linguistic phenomena and the “reality” that is supposed to be thereby described. I think some considerations from the analyses of the mass-count distinction can shed some light on that very dark topic.

We propose a shift in perspective from the view of natural languages as formal languages to natural languages as a collection of resources for constructing local languages for use in particular situations. This is suggested by our experience constructing natural language grammars for particular applications using the Grammatical Framework. It points to a research programme investigating how such resources play a role in linguistic innovation by agents constructing situation-specific local languages and how (...) they can be made dynamic, modified by the linguistic agent’s exposure to innovative linguistic data. (shrink)

The present paper intends to draw the conception of language implied in the technique of word embeddings that supported the recent development of deep neural network models in computational linguistics. After a preliminary presentation of the basic functioning of elementary artificial neural networks, we introduce the motivations and capabilities of word embeddings through one of its pioneering models, word2vec. To assess the remarkable results of the latter, we inspect the nature of its underlying mechanisms, which have been characterized as the (...) implicit factorization of a word-context matrix. We then discuss the ordinary association of the “distributional hypothesis” with a “use theory of meaning,” often justifying the theoretical basis of word embeddings, and contrast them to the theory of meaning stemming from those mechanisms through the lens of matrix models (such as vector space models and distributional semantic models). Finally, we trace back the principles of their possible consistency through Harris’s original distributionalism up to the structuralist conception of language of Saussure and Hjelmslev. Other than giving access to the technical literature and state of the art in the field of natural language processing to non-specialist readers, the paper seeks to reveal the conceptual and philosophical stakes involved in the recent application of new neural network techniques to the computational treatment of language. (shrink)

This article contains the results of a theoretical analysis of the phenomenon of natural language understanding (NLU), as a methodological problem. The combination of structural-ontological and informational-psychological approaches provided an opportunity to describe the subject matter field of NLU, as a composite function of the mind, which systemically combines the verbal and discursive structural layers. In particular, the idea of NLU is presented, on the one hand, as the relation between the discourse of a specific speech message and the (...) meta-discourse of a language, in turn, activated by the need-motivational factors. On the other hand, it is conceptualized as a process with a specific structure of information metabolism, the study of which implies the necessity to differentiate the affective (emotional) and need-motivational influences on the NLU, as well as to take into account their interaction. At the same time, the hypothesis about the influence of needs on NLU under the scenario similar to the pattern of Yerkes-Dodson is argued. And the theoretical conclusion that emotions fulfill the function of the operator of the structural features of the information metabolism of NLU is substantiated. Thus, depending on the modality of emotions in the process of NLU, it was proposed to distinguish two scenarios for the implementation of information metabolism - reduction and synthetic. The argument in favor of the conclusion about the productive and constitutive role of emotions in the process of NLU is also given. (shrink)

Natural language processing (NLP) has undergone significant changes in its methods, reflecting advances in computing technology and cognitive research. This article reviews the key stages of the evolution of natural language processing methods. The article touches on the topic of the first NLP systems developed, provides justification for the reasons for the complexity of some processed texts and the possible depth of analysis. In addition, it describes not only NLP methods before and after the GPT revolution, but also (...) current trends and prospects in the field of natural language processing. The article allows us to trace how the idea of natural language text has changed during the development of computer analysis methods, as well as to understand what text is in the mirror of natural language processing, what is really the subject of natural language processing research and what cannot be seen through the eyes of a simple researcher who does not use NLP methods. (shrink)

The paper argues that natural language quantification, as expressed by determiner phrases, is not polysemous. The foil for this claim is Hofweber, who contends that natural language quantification is polysemous between a domain reading and an inferential reading. The thesis is intended to support a more general division between externalist and internalist positions in semantics. The paper, to the contrary, argues that there is no linguistic evidence for polysemous quantification, and Hofweber’s proposal proves to be non-compositional. Further, an (...) approach at least consistent with internalism is available independent of an inferential reading, for natural language quantification can be read as ontologically neutral, which removes the rationale for the polysemy hypothesis. The paper remains neutral on so-called heavyweight vs. lightweight construals of quantification, which are not claims about natural language semantics. (shrink)

In Book II of the _Essay_, at the beginning of his discussion of language in Chapter II ("Of the Signification of Words"), John Locke writes that we humans have a variety of thoughts which might profit others, but that unfortunately these thoughts lie invisible and hidden from others. And so we use language to communicate these thoughts. As a result, "words, in their primary or immediate signification,stand for nothing but _the ideas in the mind of him that uses them_.

This paper presents two projects concerned with the application of natural language processing technology for improving communication between Public Administration and citizens. The first project, GIST,is concerned with automatic multilingual generation of instructional texts for form-filling. The second project, TAMIC, aims at providing an interface for interactive access to information, centered on natural language processing and supposed to be used by the clerk but with the active participation of the citizen.

Natural languages are vehicles of information, arguably the most important, certainly the most ubiquitous that humans possess. Our everyday interactions with the world, with each other and with ourselves depend on them. And even where in the specialised contexts of science we use dedicated formalisms to convey information, their use is embedded in natural language. This omnipresence of natural language is due in large part to its flexibility, which is almost always a virtue, sometimes a vice. (...) Natural languages are able to carry information in a wide variety of ways, about a seemingly unlimited range of topics, which makes them both efficient and versatile, and hence useful in almost every circumstance. But sometimes, when pinpoint precision is what counts, this versatility can get in the.. (shrink)

Frege's invention of the predicate calculus has been the most influential event in the history of modern logic. The calculus’ place in logic is so central that many philosophers think, in fact, of it when they think of logic. This book challenges the position in contemporary logic and philosophy of language of the predicate calculus claiming that it is based on mistaken assumptions. Ben-Yami shows that the predicate calculus is different from natural language in its fundamental semantic charac.

A trait is of adaptive value if it confers a fitness advantage to its possessor. Thus adaptiveness is an ahistorical identification of a trait affording some selective advantage to an agent within some particular environment. In results reported here we identify a trait within natural language discourse as having adaptive value by computing a trait/fitness covariance; the possession of the trait correlates with the replication success of the trait’s possessor. We show that the trait covaries with fitness across multiple (...) unrelated discursive groups. In our analysis the trait in question is a particular statistically derived word-in-context, that is, a word set. Variation of the word-usage is measured as the relative presence of the word set within a particular text, that is, the percentage of the text devoted to this set of words. Fitness is measured as the rate in which the text is responded to, or replicates, within an online environment. Thus we are studying the micro-evolutionary dynamics of natural language discourse. (shrink)

This Special Issue on Connectionist Models of Human Language Processing provides an opportunity for an appraisal both of specific connectionist models and of the status and utility of connectionist models of language in general. This introduction provides the background for the papers in the Special Issue. The development of connectionist models of language is traced, from their intellectual origins, to the state of current research. Key themes that arise throughout different areas of connectionist psycholinguistics are highlighted, and recent developments in (...) speech processing, morphology, sentence processing, language production, and reading are described. We argue that connectionist psycholinguistics has already had a significant impact on the psychology of language, and that connectionist models are likely to have an important influence on future research. (shrink)

The contract review process can be a costly and time-consuming task for lawyers and clients alike, requiring significant effort to identify and evaluate the legal implications of individual clauses. To address this challenge, we propose the use of natural language processing techniques, specifically text classification based on deontic tags, to streamline the process. Our research question is whether natural language processing techniques, specifically dense vector embeddings, can help semi-automate the contract review process and reduce time and costs for (...) legal professionals reviewing deontic modalities in contracts. In this study, we create a domain-specific dataset and train both baseline and neural network models for contract sentence classification. This approach offers a more efficient and cost-effective solution for contract review, mimicking the work of a lawyer. Our approach achieves an accuracy of 0.90, showcasing its effectiveness in identifying and evaluating individual contract sentences. (shrink)

A short time ago, D. D. Lee wrote in Philosophy of Science: “Grammar contains in crystallized form the accumulated and accumulating experience, the Weltanschauung of a people.“ He thus called our attention once more to a theme which was much discussed during the 19th century but which has been in disrepute for some time in philosophical circles. It is a theme, however, which is not without merit. More than seven years of intensive study of primitive languages have convinced me (...) that the work started by Wilhelm von Humboldt deserves serious consideration even at present, and from the ethnological as well as from the philosophical point of view. (shrink)

Abbott replies to each of Hauser's arguments. Problem solving by chimpanzees and evidence of recursion in the thought of a feral human being suggest that natural language is not necessary for productive thought. Communication would be trivial if the inner language were the outer language, but it is not. The decryption analogy Hauser uses is flawed, and it is not clear which way Occam's razor cuts.

Using contemporary science, the paper builds on Wittgenstein’s views of human language. Rather than ascribing reality to inscription-like entities, it links embodiment with distributed cognition. The verbal or (quasi) technological aspect of language is traced to not action, but human specific interactivity. This species-specific form of sense-making sustains, among other things, using texts, making/construing phonetic gestures and thinking. Human action is thus grounded in appraisals or sense-saturated coordination. To illustrate interactivity at work, the paper focuses on a case study. Over (...) 11 s, a crime scene investigator infers that she is probably dealing with an inside job: she uses not words, but intelligent gaze. This connects professional expertise to circumstances and the feeling of thinking. It is suggested that, as for other species, human appraisal is based in synergies. However, since the verbal aspect of language constrains action and thinking, we also develop customary ways of behaving. Humans extend embodiment by linking real-time activity to actions through which the collectivity imposes a variable degree of control over how individuals realise values. (shrink)