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.

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)

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.

This paper develops a natural-language agent-based model of argumentation (ABMA). Its artificial deliberative agents (ADAs) are constructed with the help of so-called neural language models recently developed in AI and computational linguistics. ADAs are equipped with a minimalist belief system and may generate and submit novel contributions to a conversation. The natural-language ABMA allows us to simulate collective deliberation in English, i.e. with arguments, reasons, and claims themselves — rather than with their mathematical representations (as (...) in symbolic models). This paper uses the natural-language ABMA to test the robustness of symbolic reason-balancing models of argumentation (Mäs & Flache 2013; Singer et al. 2019): First of all, as long as ADAs remain passive, confirmation bias and homophily updating trigger polarization, which is consistent with results from symbolic models. However, once ADAs start to actively generate new contributions, the evolution of a conversation is dominated by properties of the agents as authors. This suggests that the creation of new arguments, reasons, and claims critically affects a conversation and is of pivotal importance for understanding the dynamics of collective deliberation. The paper closes by pointing out further fruitful applications of the model and challenges for future research. (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.

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 (...) class='Hi'>natural language ontology is important, and what may be distinctive of the ontological categories and structures reflected in natural language. (shrink)

This paper is a reflexion on the computability of natural language semantics. It does not contain a new model or new results in the formal semantics of natural language: it is rather a computational analysis, in the context for type-logical grammars, of the logical models and algorithms currently used in natural language semantics, defined as a function from a grammatical sentence to a set of logical formulas—because a statement can be ambiguous, it can correspond (...) to multiple formulas, one for each reading. We argue that as long as we do not explicitly compute the interpretation in terms of possible world models, one can compute the semantic representation of a given statement, including aspects of lexical meaning. This is a very generic process, so the results are, at least in principle, widely applicable. We also discuss the algorithmic complexity of this process. (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)

A BSTRACT. We present Property Theory with Curry Typing, an intensional first-order logic for natural language semantics. PTCT permits fine-grained specifications of meaning. It also supports polymorphic types and separation types.1 We develop an intensional number theory within PTCT in order to represent proportional generalized quantifiers like most. We use the type system and our treatment of generalized quantifiers in natural language to construct a typetheoretic approach to pronominal anaphora that avoids some of the difficulties that (...) undermine previous type-theoretic analyses of this phenomenon. (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)

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)

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)

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 (...) class='Hi'>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)

This paper seeks to contribute to the sociology of nations, a literature that is only starting to carve out its place in the social sciences. The paper offers a reconceptualization of “nations” as “national cultures”, employing an evolutionary perspective and a systemic framework in which “nations” are understood as cultural systems of a special kind. National cultures are intimately tied to natural languages, and the acquisition of a national culture occurs as part and parcel of the acquisition of a (...) natural language. Acquiring a natural language is a prerequisite for learning other cultural systems (artefactual languages as well as other natural languages). National cultures function as metacultures. They are also the reference cultures for modern states and their citizens, a political dimension of nations that is of paramount importance, though it will only be touched on in this paper. National cultures should be considered as the most fundamental type of cultural system today. (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)

_Natural Language and Possible Minds: How Language Uncovers the Cognitive Landscape of Nature_ examines the intrinsic connection between natural language and the nature of mentality, offering to show how language can shed light on the forms of other types of mentality in non-humans.

Progress in philosophy is difficult to achieve because our methods are evidentially and rhetorically weak. In the last two decades, experimental philosophers have begun to employ the methods of the social sciences to address philosophical questions. However, the adequacy of these methods has been called into question by repeated failures of replication. Experimental philosophers need to incorporate more robust methods to achieve a multi-modal perspective. In this chapter, we describe and showcase cutting-edge methods for data-mining and visualization. Big data is (...) a useful investigatory tool for moral psychology, and it fits well with the Ramsification method the first author advances in a series of recent papers. The guiding insight of these papers is that we can infer the meaning and structure of concepts from patterns of assertions and inferential associations in natural language. (shrink)

With the growing use of the Social Web, an increasing number of applications for exchanging opinions with other people are becoming available online. These applications are widely adopted with the consequence that the number of opinions about the debated issues increases. In order to cut in on a debate, the participants need first to evaluate the opinions of the other users to detect whether they are in favour or against the debated issue. Bipolar argumentation proposes algorithms and semantics to evaluate (...) the set of accepted arguments, given the support and the attack relations among them. Two main problems arise. First, an automated framework to detect the relations among the arguments represented by the natural language (NL) formulation of the users’ opinions is needed. Our paper addresses this open issue by proposing and evaluating the use of NL techniques to identify the arguments and their relations. In particular, we adopt the textual entailment (TE) approach, a generic framework for applied semantics, where linguistic objects are mapped by means of semantic inferences at a textual level. TE is then coupled together with an abstract bipolar argumentation system which allows to identify the arguments that are accepted in the considered online debate. Second, we address the problem of studying and comparing the different proposals put forward for modelling the support relation. The emerging scenario shows that there is not a unique interpretation of the support relation. In particular, different combinations of additional attacks among the arguments involved in a support relation are proposed. We provide an NL account of the notion of support based on online debates, by discussing and evaluating the support relation among arguments with respect to the more specific notion of TE in the NL processing field. Finally, we carry out a comparative evaluation of four proposals of additional attacks on a sample of NL arguments extracted from Debatepedia. The originality of the proposed framework lies in the following point: NL debates are analysed and the relations among the arguments are automatically extracted. (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)

This chapter contains sections titled: What are the Constraints on Formal Representations? What is the Relationship between a Natural Language Sentence and its Formal Representation?

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.

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)

This paper describes a prototype implementation of a Labelled Deduction System for natural language interpretation, where interpretation is taken to be the process of understanding a natural language utterance. The implementation models the process of understanding wh-gap dependencies in questions and relative clauses for a fragment of English. The paper is divided in three main sections. In Section 1, we introduce the basic architecture of the system. Section 2 outlines a prototype implementation of wh-binding and indicates (...) its potential for explanation of linguistic phenomena, and in Section 3 we briefly set the model within a large theoretical perspective, comparing it to other type-logical approaches to natural language analysis. (shrink)

This work presents the structure, distribution and semantic interpretation of quantificational expressions in languages from diverse language families and typological profiles. The current volume pays special attention to underrepresented languages of different status and endangerment level. Languages covered include American and Russian Sign Languages, and sixteen spoken languages from Africa, Australia, Papua, the Americas, and different parts of Asia. The articles respond to a questionnaire the editors constructed to enable detailed crosslinguistic comparison of numerous features. They offer comparable information (...) on semantic classes of quantifiers (generalized existential, generalized universal, proportional, partitive), syntactically complex quantifiers (intensive modification, Boolean compounds, exception phrases, et cetera), and several more specific issues such as quantifier scope ambiguities, floating quantifiers, and binary (type 2) quantifiers. The book is intended for semanticists, logicians interested in quantification in natural language, and general linguists as articles are meant to be descriptive and theory independent. The book continues and expands the coverage of the Handbook of Quantifiers in Natural Language (2012) by the same editors, and extends the earlier work in Matthewson (2008), Gil and others (2013) and Bach et al (1995). (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)

This article presents an architecture for natural language generation of biomedical argumentation. The goal is to reconstruct the normative arguments that a domain expert would provide, in a manner that is transparent to a lay audience. Transparency means that an argument's structure and functional components are accessible to its audience. Transparency is necessary before an audience can fully comprehend, evaluate or challenge an argument, or re-evaluate it in light of new findings about the case or changes in scientific (...) knowledge. The architecture has been implemented and evaluated in the Genetics Information Expression Assistant, a prototype system for drafting genetic counselling patient letters. Argument generation makes use of abstract argumentation schemes. Derived from the analysis of arguments used in genetic counselling, these mainly causal argument patterns refer to abstract properties of qualitative causal domain models. (shrink)

It is common in contemporary metaphysics to distinguish two levels of ontology: the ontology of ordinary objects and the ontology of fundamental reality. This papers argues that natural language reflects not only the ontology of ordinary objects, but also a language-driven ontology, which is involved in the mass-count distinction and part-structure-sensitive semantic selection, as well as perhaps the light ontology of pleonastic entities. The paper recasts my older theory of situated part structures without situations, making use of (...) a primitive notion of unity. (shrink)

Knowledge is power. Knowledge about human psychology is increasingly being produced using natural language processing (NLP) and related techniques. The power that accompanies and harnesses this knowledge should be subject to ethical controls and oversight. In this chapter, we address the ethical pitfalls that are likely to be encountered in the context of such research. These pitfalls occur at various stages of the NLP pipeline, including data acquisition, enrichment, analysis, storage, and sharing. We also address secondary uses of (...) the results and tools developed through psychometric NLP, such as profit-driven targeted advertising, political campaigns, and domestic and international psyops. Along the way, we reflect on potential ethical guidelines and considerations that may help researchers navigate these pitfalls. (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. (shrink)

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)

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.

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)

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)

Is medieval logic formal? And if yes, in what sense? There are striking affinities between medieval and contemporary theories of language. Authors from the two periods share formal ambitions and maintain complex, and at time uneasy, relations with natural language. However, modern scholars became careful not to overlook the specificities of theories developed more than five hundred years apart, in particular with respect to their 'formal' character. In 1972, Alfonso Maieru noted that the efforts of medieval logicians (...) to identify logical structures in language which are formal enough to become objects of scientific consideration. He also stressed that the language investigated is a historical one, Latin, so that one can legitimately wonder to which extent... one is allowed to speak of 'formal logic' in the middle ages. In other words, medieval logic is characterized by a tension between 'formalist ambitions' and constraints proper to natural language. Today, our knowledge of the field has considerably expanded, calling for a new assessment of the question. (shrink)

This text offers an innovative approach to the teaching of logic, which is rigorous but entirely non-symbolic. By introducing students to deductive inferences in natural language, the book breaks new ground pedagogically. Cannon focuses on such topics as using a tableaux technique to assess inconsistency; using generative grammar; employing logical analyses of sentences; and dealing with quantifier expressions and syllogisms. An appendix covers truth-functional logic.

Recent work on compositional distributional models shows that bialgebras over finite dimensional vector spaces can be applied to treat generalised quantifiersGeneralised quantifiers for natural language. That technique requires one to construct the vector space over powersets, and therefore is computationally costly. In this paper, we overcome this problem by considering fuzzy versions of quantifiers along the lines of ZadehZadeh, L. A., within the category of many valued relationsMany valued relations. We show that this category is a concrete instantiation (...) of the compositional distributional model. We show that the semantics obtained in this model is equivalent to the semantics of the fuzzy quantifiers of ZadehZadeh, L. A.. As a result, we are now able to treat fuzzy quantification without requiring a powerset construction. (shrink)

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)

A formal, computational, semantically clean representation of natural language is presented. This representation captures the fact that logical inferences in natural language crucially depend on the semantic relation of entailment between sentential constituents such as determiner, noun, adjective, adverb, preposition, and verb phrases.The representation parallels natural language in that it accounts for human intuition about entailment of sentences, it preserves its structure, it reflects the semantics of different syntactic categories, it simulates conjunction, disjunction, and (...) negation in natural language by computable operations with provable mathematical properties, and it allows one to represent coordination on different syntactic levels. (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.