Some recent studies in computationallinguistics have aimed to take advantage of various cues presented by punctuation marks. This short survey is intended to summarise these research efforts and additionally, to outline a current perspective for the usage and functions of punctuation marks. We conclude by presenting an information-based framework for punctuation, influenced by treatments of several related phenomena in computationallinguistics.
Lexical semantics has become a major research area within computationallinguistics, drawing from psycholinguistics, knowledge representation, computer algorithms and architecture. Research programmes whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored.Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerised lexicons (...) for the automatic treatment of natural language, with applications to machine translation, automatic indexing, and database front-ends, knowledge extraction, among other things. It focuses on semantic issues, as seen by linguists, psychologists, and computer scientists. Besides describing academic research, it also covers ongoing industrial projects. (shrink)
Narrative passages told from a character's perspective convey the character's thoughts and perceptions. We present a discourse process that recognizes characters' thoughts and perceptions in third-person narrative. An effect of perspective on reference in narrative is addressed: References in passages told from the perspective of a character reflect the character's beliefs. An algorithm that uses the results of our discourse process to understand references with respect to an appropriate set of beliefs is presented.
There is currently much interest in bringing together the tradition of categorial grammar, and especially the Lambek calculus, with the recent paradigm of linear logic to which it has strong ties. One active research area is designing non-commutative versions of linear logic (Abrusci, 1995; Retoré, 1993) which can be sensitive to word order while retaining the hypothetical reasoning capabilities of standard (commutative) linear logic (Dalrymple et al., 1995). Some connections between the Lambek calculus and computations in groups have long been (...) known (van Benthem, 1986) but no serious attempt has been made to base a theory of linguistic processing solely on group structure. This paper presents such a model, and demonstrates the connection between linguistic processing and the classical algebraic notions of non-commutative free group, conjugacy, and group presentations. A grammar in this model, or G-grammar is a collection of lexical expressions which are products of logical forms, phonological forms, and inverses of those. Phrasal descriptions are obtained by forming products of lexical expressions and by cancelling contiguous elements which are inverses of each other. A G-grammar provides a symmetrical specification of the relation between a logical form and a phonological string that is neutral between parsing and generation modes. We show how the G-grammar can be oriented for each of the modes by reformulating the lexical expressions as rewriting rules adapted to parsing or generation, which then have strong decidability properties (inherent reversibility). We give examples showing the value of conjugacy for handling long-distance movement and quantifier scoping both in parsing and generation. The paper argues that by moving from the free monoid over a vocabulary V (standard in formal language theory) to the free group over V, deep affinities between linguistic phenomena and classical algebra come to the surface, and that the consequences of tapping the mathematical connections thus established can be considerable. (shrink)
We combine state-of-the-art techniques from computational linguisticsand theorem proving to build an engine for playing text adventures,computer games with which the player interacts purely through naturallanguage. The system employs a parser for dependency grammar and ageneration system based on TAG, and has components for resolving andgenerating referring expressions. Most of these modules make heavy useof inferences offered by a modern theorem prover for descriptionlogic. Our game engine solves some problems inherent in classical textadventures, and is an interesting test case (...) for the interactionbetween natural language processing and inference. (shrink)
This book deals with a major problem in the study of language: the problem of reference. The ease with which we refer to things in conversation is deceptive. Upon closer scrutiny, it turns out that we hardly ever tell each other explicitly what object we mean, although we expect our interlocutor to discern it. Amichai Kronfeld provides an answer to two questions associated with this: how do we successfully refer, and how can a computer be programmed to achieve this? Beginning (...) with the major theories of reference, Dr Kronfeld provides a consistent philosophical view which is a synthesis of Frege's and Russell's semantic insights with Grice's and Searle's pragmatic theories. This leads to a set of guiding principles, which are then applied to a computational model of referring. The discussion is made accessible to readers from a number of backgrounds: in particular, students and researchers in the areas of computationallinguistics, artificial intelligence and the philosophy of language will want to read this book. (shrink)
This volume is a collection of original contributions from outstanding scholars in linguistics, philosophy and computationallinguistics exploring the relation between word meaning and human linguistic creativity. The papers present different aspects surrounding the question of what is word meaning, a problem that has been the center of heated debate in all those disciplines that directly or indirectly are concerned with the study of language and of human cognition. The discussions are centered around the newly emerging view (...) of the mental lexicon, as outlined in the Generative Lexicon theory (Pustejovsky, 1995), which proposes a unified model for defining word meaning. The individual contributors present their evidence for a generative approach as well as critical perspectives, which provides for a volume where word meaning is not viewed only from a particular angle or from a particular concern, but from a wide variety of topics, each introduced and explained by the editors. (shrink)
The first of its kind to thoroughly cover language technology at all levels and with all modern technologies this book takes an empirical approach to the ...
Some of the systems used in natural language generation (NLG), a branch of applied computationallinguistics, have the capacity to create or assemble somewhat original messages adapted to new contexts. In this paper, taking Bernard Williams’ account of assertion by machines as a starting point, I argue that NLG systems meet the criteria for being speech actants to a substantial degree. They are capable of authoring original messages, and can even simulate illocutionary force and speaker meaning. Background intelligence (...) embedded in their datasets enhances these speech capacities. Although there is an open question about who is ultimately responsible for their speech, if anybody, we can settle this question by using the notion of proxy speech, in which responsibility for artificial speech acts is assigned legally or conventionally to an entity separate from the speech actant. (shrink)
A primary problem in the area of natural language processing has been semantic analysis. This book looks at the semantics of natural languages in context. It presents an approach to the computational processing of English text that combines current theories of knowledge representation and reasoning in Artificial Intelligence with the latest linguistic views of lexical semantics. The book will interest postgraduates and researchers in computationallinguistics as well as industrial research groups specializing in natural language processing.
We study the computational complexity of polyadic quantifiers in natural language. This type of quantification is widely used in formal semantics to model the meaning of multi-quantifier sentences. First, we show that the standard constructions that turn simple determiners into complex quantifiers, namely Boolean operations, iteration, cumulation, and resumption, are tractable. Then, we provide an insight into branching operation yielding intractable natural language multi-quantifier expressions. Next, we focus on a linguistic case study. We use computational complexity results to (...) investigate semantic distinctions between quantified reciprocal sentences. We show a computational dichotomy<br>between different readings of reciprocity. Finally, we go more into philosophical speculation on meaning, ambiguity and computational complexity. In particular, we investigate a possibility to<br>revise the Strong Meaning Hypothesis with complexity aspects to better account for meaning shifts in the domain of multi-quantifier sentences. The paper not only contributes to the field of the formal<br>semantics but also illustrates how the tools of computational complexity theory might be successfully used in linguistics and philosophy with an eye towards cognitive science. (shrink)
Corpus-driven Cognitive Semantics Introduction to the field Dylan Glynn Is quantitative empirical research possible for the study of semantics?1 More ...
In the dissertation we study the complexity of generalized quantifiers in natural language. Our perspective is interdisciplinary: we combine philosophical insights with theoretical computer science, experimental cognitive science and linguistic theories. -/- In Chapter 1 we argue for identifying a part of meaning, the so-called referential meaning (model-checking), with algorithms. Moreover, we discuss the influence of computational complexity theory on cognitive tasks. We give some arguments to treat as cognitively tractable only those problems which can be computed in polynomial (...) time. Additionally, we suggest that plausible semantic theories of the everyday fragment of natural language can be formulated in the existential fragment of second-order logic. -/- In Chapter 2 we give an overview of the basic notions of generalized quantifier theory, computability theory, and descriptive complexity theory. -/- In Chapter 3 we prove that PTIME quantifiers are closed under iteration, cumulation and resumption. Next, we discuss the NP-completeness of branching quantifiers. Finally, we show that some Ramsey quantifiers define NP-complete classes of finite models while others stay in PTIME. We also give a sufficient condition for a Ramsey quantifier to be computable in polynomial time. -/- In Chapter 4 we investigate the computational complexity of polyadic lifts expressing various readings of reciprocal sentences with quantified antecedents. We show a dichotomy between these readings: the strong reciprocal reading can create NP-complete constructions, while the weak and the intermediate reciprocal readings do not. Additionally, we argue that this difference should be acknowledged in the Strong Meaning hypothesis. -/- In Chapter 5 we study the definability and complexity of the type-shifting approach to collective quantification in natural language. We show that under reasonable complexity assumptions it is not general enough to cover the semantics of all collective quantifiers in natural language. The type-shifting approach cannot lead outside second-order logic and arguably some collective quantifiers are not expressible in second-order logic. As a result, we argue that algebraic (many-sorted) formalisms dealing with collectivity are more plausible than the type-shifting approach. Moreover, we suggest that some collective quantifiers might not be realized in everyday language due to their high computational complexity. Additionally, we introduce the so-called second-order generalized quantifiers to the study of collective semantics. -/- In Chapter 6 we study the statement known as Hintikka's thesis: that the semantics of sentences like ``Most boys and most girls hate each other'' is not expressible by linear formulae and one needs to use branching quantification. We discuss possible readings of such sentences and come to the conclusion that they are expressible by linear formulae, as opposed to what Hintikka states. Next, we propose empirical evidence confirming our theoretical predictions that these sentences are sometimes interpreted by people as having the conjunctional reading. -/- In Chapter 7 we discuss a computational semantics for monadic quantifiers in natural language. We recall that it can be expressed in terms of finite-state and push-down automata. Then we present and criticize the neurological research building on this model. The discussion leads to a new experimental set-up which provides empirical evidence confirming the complexity predictions of the computational model. We show that the differences in reaction time needed for comprehension of sentences with monadic quantifiers are consistent with the complexity differences predicted by the model. -/- In Chapter 8 we discuss some general open questions and possible directions for future research, e.g., using different measures of complexity, involving game-theory and so on. -/- In general, our research explores, from different perspectives, the advantages of identifying meaning with algorithms and applying computational complexity analysis to semantic issues. It shows the fruitfulness of such an abstract computational approach for linguistics and cognitive science. (shrink)
Panini’s 5th century BC generative Sanskrit grammar is shown to be sufficient to describe any formal or computational system in oral form, using a new observation regarding Panini’s “auxilary markers” and the methods of Post production systems. Modern universal computation is described using rules modeled on Sanskrit positional number words representing large numbers in versified sutras. Two versions of “Panini arithmetic” are defined to contrast the computational strength of non-positional and positional numeration. The computational increase between additive (...) and multiplicative arithmetic is attributed to the cognitive skills required for the grammaticalization of positional number words. Positional notations are formally described using Presburger arithmetic and results of Fischer-Rabin on bounded multiplication. As a whole the construction shows how mathematical computation is constructed from natural language structure and the cognitive skills needed for language use. The modern origins of generative linguistics and Turing’s universal computation are described in a new historical light, with Indian positional notation providing computational expertise needed for modern logic. The paper will interest Sanskritists, computer scientists and logicians, and cognitive linguists. No knowledge of Panini grammar, Sanskrit or linguistic grammaticalization is assumed. (shrink)
Polysemy is a term used in semantic and lexical analysis to describe a word with multiple meanings. Although such words present few difficulties in everyday communication, they do pose near-intractable problems for linguists and lexicographers. The contributors in this volume consider the implications of these problems for linguistic theory and how they may be addressed in computationallinguistics.
(2) Vol., Classification of Propositional Provability Logics LD Beklemishev Introduction Overview. The idea of an axiomatic approach to the study of ...
We compare our model of unsupervised learning of linguistic structures, ADIOS [1, 2, 3], to some recent work in computationallinguistics and in grammar theory. Our approach resembles the Construction Grammar in its general philosophy (e.g., in its reliance on structural generalizations rather than on syntax projected by the lexicon, as in the current generative theories), and the Tree Adjoining Grammar in its computational characteristics (e.g., in its apparent affinity with Mildly Context Sensitive Languages). The representations learned (...) by our algorithm are truly emergent from the (unannotated) corpus data, whereas those found in published works on cognitive and construction grammars and on TAGs are hand-tailored. Thus, our results complement and extend both the computational and the more linguistically oriented research into language acquisition. We conclude by suggesting how empirical and formal study of language can be best integrated. (shrink)
Many of the formalisms used in Attribute Value grammar are notational variants of languages of propositional modal logic, and testing whether two Attribute Value Structures unify amounts to testing for modal satisfiability. In this paper we put this observation to work. We study the complexity of the satisfiability problem for nine modal languages which mirror different aspects of AVS description formalisms, including the ability to express re-entrancy, the ability to express generalisations, and the ability to express recursive constraints. Two main (...) techniques are used: either Kripke models with desirable properties are constructed, or modalities are used to simulate fragments of Propositional Dynamic Logic. Further possibilities for the application of modal logic in computationallinguistics are noted. (shrink)
Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM (Shieber 1994a, 1994b; Loebner 1994).1 With this collection, I expect it to become equally well known to philosophers.
This book introduces the most important problems of reference and considers the solutions that have been proposed to explain them. Reference is at the centre of debate among linguists and philosophers and, as Barbara Abbott shows, this has been the case for centuries. She begins by examining the basic issue of how far reference is a two place (words-world) or a three place (speakers-words-world) relation. She then discusses the main aspects of the field and the issues associated with them, including (...) those concerning proper names; direct reference and individual concepts; the difference between referential and quantificational descriptions; pronouns and indexicality; concepts like definiteness and strength; and noun phrases in discourse. Professor Abbott writes with exceptional verve and wit. She presupposes no technical knowledge or background and presents issues and analyses from first principles, illustrating them at every stage with well-chosen examples. Her book is addressed in the first place to advanced undergraduate and graduate students in linguistics and philosophy of language, but it will also appeal to students and practitioners in computationallinguistics, cognitive psychology, and anthropology. All will welcome the clarity this guide brings to a subject that continues to challenge the leading thinkers of the age. (shrink)
In this paper, I argue for a modified version of what Devitt (2006) calls the Representational Thesis (RT). According to RT, syntactic rules or principles are psychologically real, in the sense that they are represented in the mind/brain of every linguistically competent speaker/hearer. I present a range of behavioral and neurophysiological evidence for the claim that the human sentence processing mechanism constructs mental representations of the syntactic properties of linguistic stimuli. I then survey a range of psychologically plausible computational (...) models of comprehension and show that they are all committed to RT. I go on to sketch a framework for thinking about the nature of the representations involved in sentence processing. My claim is that these are best characterized not as propositional attitudes but, rather, as subpersonal states whose representational properties are determined by their functional role. Finally, I distinguish between explicit and implicit representations and argue that the latter can be drawn on as data by the algorithms that constitute our sentence processing routines. I conclude that skepticism concerning the psychological reality of grammars cannot be sustained. (shrink)
The ability to produce and understand referring expressions is basic to human language use and human cognition. Reference comprises the ability to think of and represent objects (both real and imagined/fictional), to indicate to others which of these objects we are talking about, and to determine what others are talking about when they use a nominal expression. The articles in this volume are concerned with some of the central themes and challenges in research on reference within the cognitive sciences - (...) philosophy (including philosophy of language and mind, logic, and formal semantics), theoretical and computationallinguistics, and cognitive psychology. The papers address four basic questions: What is reference? What is the appropriate analysis of different referring forms, such as definite descriptions? How is reference resolved? and How do speaker/writers select appropriate referring forms, such as pronouns vs. full noun phrases, demonstrative vs. personal pronouns, and overt vs. null/zero pronominal forms? Some of the papers assume and build on existing theories, such as Centering Theory and the Givenness Hierarchy framework; others propose their own models of reference understanding or production. The essays examine reference from a number of disciplinary and interdisciplinary perspectives, informed by different research traditions and employing different methodologies. While the contributors to the volume were primarily trained in one of the four represented disciplines-computer science, linguistics, philosophy and psychology, and use methodologies typical of that discipline, each of them bridges more than one discipline in their methodology and/or their approach. (shrink)
For the past three decades linguistic theory has been based on the assumption that sentences are interpreted and constructed by the brain by means of computational processes analogous to those of a serial-digital computer. The recent interest in devices based on the neural network or parallel distributed processor (PDP) principle raises the possibility ("eliminative connectionism") that such devices may ultimately replace the S-D computer as the model for the interpretation and generation of language by the brain. An analysis of (...) the differences between the two models suggests that the effect of such a development would be to steer linguistic theory towards a return to the empiricism and behaviorism which prevailed before it was driven by Chomsky towards nativism and mentalism. Linguists, however, will not be persuaded to return to such a theory unless and until it can deal with the phenomenon of novel sentence construction as effectively as its nativist/mentalist rival. (shrink)
While situation theory and situation semantics provide an appropriate framework for a realistic model-theoretic treatment of natural language, serious thinking on their `computational' aspects has just started. Existing proposals mainly offer a Prolog- or Lisp-like programming environment with varying degrees of divergence from the ontology of situation theory. In this paper, we introduce a computational medium (called BABY-SIT) based on situations. The primary motivation underlying BABY-SIT is to facilitate the development and testing of programs in domains ranging from (...)linguistics to artificial intelligence in a unified framework built upon situation-theoretic constructs. (shrink)
It is often assumed that graphemes are a crucial level of orthographic representation above letters. Current connectionist models of reading, however, do not address how the mapping from letters to graphemes is learned. One major challenge for computational modeling is therefore developing a model that learns this mapping and can assign the graphemes to linguistically meaningful categories such as the onset, vowel, and coda of a syllable. Here, we present a model that learns to do this in English for (...) strings of any letter length and any number of syllables. The model is evaluated on error rates and further validated on the results of a behavioral experiment designed to examine ambiguities in the processing of graphemes. The results show that the model (a) chooses graphemes from letter strings with a high level of accuracy, even when trained on only a small portion of the English lexicon; (b) chooses a similar set of graphemes as people do in situations where different graphemes can potentially be selected; (c) predicts orthographic effects on segmentation which are found in human data; and (d) can be readily integrated into a full-blown model of multi-syllabic reading aloud such as CDP++ (Perry, Ziegler, & Zorzi, 2010). Altogether, these results suggest that the model provides a plausible hypothesis for the kind of computations that underlie the use of graphemes in skilled reading. (shrink)
The ultimate goal of research into computational intelligence is the construction of a fully embodied and fully autonomous artificial agent. This ultimate artificial agent must not only be able to act, but it must be able to act morally. In order to realize this goal, a number of challenges must be met, and a number of questions must be answered, the upshot being that, in doing so, the form of agency to which we must aim in developing artificial agents (...) comes into focus. This chapter explores these issues, and from its results details a novel approach to meeting the given conditions in a simple architecture of information processing. (shrink)
Written by world-leading experts, this book draws together a number of important strands in contemporary approaches to the philosophical and scientific questions that emerge when dealing with the issues of computing, information, cognition and the conceptual issues that arise at their intersections. It discovers and develops the connections at the borders and in the interstices of disciplines and debates. This volume presents a range of essays that deal with the currently vigorous concerns of the philosophy of information, ontology creation and (...) control, bioinformation and biosemiotics, computational and post-computation approaches to the philosophy of cognitive science, computationallinguistics, ethics, and education. http://www.amazon.ca/Computation-Information-Cognition-Gordana-Dodig-Crnkovic/dp/1847180906. (shrink)
We study the computational complexity of reciprocal sentences with quantified antecedents. We observe a computational dichotomy between different interpretations of reciprocity, and shed some light on the status of the so-called Strong Meaning Hypothesis.
Linguists take the intuitive judgments of speakers to be good evidence for a grammar. Why? The Chomskian answer is that they are derived by a rational process from a representation of linguistic rules in the language faculty. The paper takes a different view. It argues for a naturalistic and non-Cartesian view of intuitions in general. They are empirical central-processor responses to phenomena differing from other such responses only in being immediate and fairly unreflective. Applying this to linguistic intuitions yields an (...) explanation of their evidential role without any appeal to the representation of rules. Introduction The evidence for linguistic theories A tension in the linguists' view of intuitions Intuitions in general Linguistic intuitions Comparison of the modest explanation with the standard Cartesian explanation A nonstandard Cartesian explanation of the role of intuitions? Must linguistics explain intuitions? Conclusion. (shrink)
Advocates of the computational theory of mind claim that the mind is a computer whose operations can be implemented by various computational systems. According to these philosophers, the mind is multiply realisable because—as they claim—thinking involves the manipulation of syntactically structured mental representations. Since syntactically structured representations can be made of different kinds of material while performing the same calculation, mental processes can also be implemented by different kinds of material. From this perspective, consciousness plays a minor role (...) in mental activity. However, contemporary neuroscience provides experimental evidence suggesting that mental representations necessarily involve consciousness. Consciousness does not only enable individuals to become aware of their own thoughts, it also constantly changes the causal properties of these thoughts. In light of these empirical studies, mental representations appear to be intrinsically dependent on consciousness. This discovery represents an obstacle to any attempt to construct an artificial mind. (shrink)
Michael Devitt has argued that Chomsky, along with many other Linguists and philosophers, is ignorant of the true nature of Generative Linguistics. In particular, Devitt argues that Chomsky and others wrongly believe the proper object of linguistic inquiry to be speakers' competences, rather than the languages that speakers are competent with. In return, some commentators on Devitt's work have returned the accusation, arguing that it is Devitt who is ignorant about Linguistics. In this note, I consider whether there (...) might be less to this apparent dispute than meets the eye. -/- . (shrink)
The Language of Thought program has a suicidal edge. Jerry Fodor, of all people, has argued that although LOT will likely succeed in explaining modular processes, it will fail to explain the central system, a subsystem in the brain in which information from the different sense modalities is integrated, conscious deliberation occurs, and behavior is planned. A fundamental characteristic of the central system is that it is “informationally unencapsulated” -- its operations can draw from information from any cognitive domain. The (...) domain general nature of the central system is key to human reasoning; our ability to connect apparently unrelated concepts enables the creativity and flexibility of human thought, as does our ability to integrate material across sensory divides. The central system is the holy grail of cognitive science: understanding higher cognitive function is crucial to grasping how humans reach their highest intellectual achievements. But according to Fodor, the founding father of the LOT program and the related Computational Theory of Mind (CTM), the holy grail is out of reach: the central system is likely to be non-computational (Fodor 1983, 2000, 2008). Cognitive scientists working on higher cognitive function should abandon their efforts. Research should be limited to the modules, which for Fodor rest at the sensory periphery (2000).1 Cognitive scientists who work in the symbol processing tradition outside of philosophy would reject this pessimism, but ironically, within philosophy itself, this pessimistic streak has been very influential, most likely because it comes from the most well-known proponent of LOT and CTM. Indeed, pessimism about centrality has become assimilated into the mainstream conception of LOT. (Herein, I refer to a LOT that appeals to pessimism about centrality as the “standard LOT”). I imagine this makes the standard LOT unattractive to those philosophers with a more optimistic approach to what cognitive science can achieve.. (shrink)
Philosophy of linguistics is the philosophy of science as applied to linguistics. This differentiates it sharply from the philosophy of language, traditionally concerned with matters of meaning and reference.
Mind–body dualism has rarely been an issue in the generative study of mind; Chomsky himself has long claimed it to be incoherent and unformulable. We first present and defend this negative argument but then suggest that the generative enterprise may license a rather novel and internalist view of the mind and its place in nature, different from all of, (i) the commonly assumed functionalist metaphysics of generative linguistics, (ii) physicalism, and (iii) Chomsky’s negative stance. Our argument departs from the (...) empirical observation that the linguistic mind gives rise to hierarchies of semantic complexity that we argue (only) follow from constraints of an essentially mathematical kind. We assume that the faculty of language tightly correlates with the mathematical capacity both formally and in evolution, the latter plausibly arising as an abstraction from the former, as a kind of specialized output. On this basis, and since the semantic hierarchies in question are mirrored in the syntactic complexity of the expression involved, we posit the existence of a higher-dimensional syntax structured on the model of the hierarchy of numbers, in order to explain the semantic facts in question. If so, syntax does not have a physicalist interpretation any more than the hierarchy of number-theoretic spaces does. (shrink)
According to some philosophers, computational explanation is proprietary to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and (...) outline some promising answers that are being developed by a number of authors. (shrink)
There is no consensus as to whether a Liar sentence is meaningful or not. Still, a widespread conviction with respect to Liar sentences (and other ungrounded sentences) is that, whether or not they are meaningful, they are useless . The philosophical contribution of this paper is to put this conviction into question. Using the framework of assertoric semantics , which is a semantic valuation method for languages of self-referential truth that has been developed by the author, we show that certain (...)computational problems, called query structures , can be solved more efficiently by an agent who has self-referential resources (amongst which are Liar sentences) than by an agent who has only classical resources; we establish the computational power of self-referential truth . The paper concludes with some thoughts on the implications of the established result for deflationary accounts of truth. (shrink)
In this paper I review some leading developments in the empirical theory of affect. I argue that (1) affect is a distinct perceptual representation governed system, and (2) that there are significant modular factors in affect. The paper concludes with the observation thatfeeler (affective perceptual system) may be a natural kind within cognitive science. The main purpose of the paper is to explore some hitherto unappreciated connections between the theory of affect and the computational theory of mind.
In this paper we explore how compositional semantics, discourse structure, and the cognitive states of participants all contribute to pragmatic constraints on answers to questions in dialogue. We synthesise formal semantic theories on questions and answers with techniques for discourse interpretation familiar from computationallinguistics, and show how this provides richer constraints on responses in dialogue than either component can achieve alone.
The paper presents a proof-theoretic semantics (PTS) for a fragment of natural language, providing an alternative to the traditional model-theoretic (Montagovian) semantics (MTS), whereby meanings are truth-condition (in arbitrary models). Instead, meanings are taken as derivability-conditions in a dedicated natural-deduction (ND) proof-system. This semantics is effective (algorithmically decidable), adhering to the meaning as use paradigm, not suffering from several of the criticisms formulated by philosophers of language against MTS as a theory of meaning. In particular, Dummett’s manifestation argument does not (...) obtain, and assertions are always warranted, having grounds of assertion. The proof system is shown to satisfy Dummett’s harmony property, justifying the ND rules as meaning conferring. The semantics is suitable for incorporation into computationallinguistics grammars, formulated in type-logical grammar. (shrink)
Despite its significance in neuroscience and computation, McCulloch and Pitts's celebrated 1943 paper has received little historical and philosophical attention. In 1943 there already existed a lively community of biophysicists doing mathematical work on neural networks. What was novel in McCulloch and Pitts's paper was their use of logic and computation to understand neural, and thus mental, activity. McCulloch and Pitts's contributions included (i) a formalism whose refinement and generalization led to the notion of finite automata (an important formalism in (...) computability theory), (ii) a technique that inspired the notion of logic design (a fundamental part of modern computer design), (iii) the first use of computation to address the mind–body problem, and (iv) the first modern computational theory of mind and brain. (shrink)
This book deals with the need to rethink the aims and methods of contemporary linguistics. Orthodox linguists' discussions of linguistic form fail to exemplify how language users become language makers. Integrationist theory is used here as a solution to this basic problem within general linguistics. The book is aimed at an interdisciplinary readership, comprising those engaged in study, teaching and research in the humanities and social sciences, including linguistics, philosophy, sociology and psychology.
We examine the verification of simple quantifiers in natural language from a computational model perspective. We refer to previous neuropsychological investigations of the same problem and suggest extending their experimental setting. Moreover, we give some direct empirical evidence linking computational complexity predictions with cognitive reality. In the empirical study we compare time needed for understanding different types of quantifiers. We show that the computational distinction between quantifiers recognized by finite-automata and push-down automata is psychologically relevant. Our research improves (...) upon hypothesis and explanatory power of recent neuroimaging studies as well as provides evidence. (shrink)
The problem of computational complexity of semantics for some natural language constructions – considered in [M. Mostowski, D. Wojtyniak 2004] – motivates an interest in complexity of Ramsey quantifiers in finite models. In general a sentence with a Ramsey quantifier R of the following form Rx, yH(x, y) is interpreted as ∃A(A is big relatively to the universe ∧A2 ⊆ H). In the paper cited the problem of the complexity of the Hintikka sentence is reduced to the problem of (...)computational complexity of the Ramsey quantifier for which the phrase “A is big relatively to the universe” is interpreted as containing at least one representative of each equivalence class, for some given equvalence relation. In this work we consider quantifiers Rf, for which “A is big relatively to the universe” means “card(A) > f (n), where n is the size of the universe”. Following [Blass, Gurevich 1986] we call R mighty if Rx, yH(x, y) defines N P – complete class of finite models. Similarly we say that Rf is N P –hard if the corresponding class is N P –hard. We prove the following theorems. (shrink)
This edited volume offers ten new essays on semantics, philosophy of language, and philosophy of linguistics by top scholars in the field. Covering a wide range of topics, the collection is sure to be of interest to scholars in those areas as well as some philosophers of mind. Because of the diversity of topics and perspectives inherent in the collection, readers will find both exposition and debate among the contributors.
We compared the processing of natural language quantifiers in a group of patients with schizophrenia and a healthy control group. In both groups, the difficulty of the quantifiers was consistent with computational predictions, and patients with schizophrenia took more time to solve the problems. However, they were significantly less accurate only with proportional quantifiers, like more than half. This can be explained by noting that, according to the complexity perspective, only proportional quantifiers require working memory engagement.
We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous (...) signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. (shrink)
This groundbreaking collection, the most thorough treatment of the philosophy of linguistics ever published, brings together philosophers, scientists and historians to map out both the foundational assumptions set during the second half of ...
In this chapter, I argue that some aspects of cognitive phenomena cannot be explained computationally. In the first part, I sketch a mechanistic account of computational explanation that spans multiple levels of organization of cognitive systems. In the second part, I turn my attention to what cannot be explained about cognitive systems in this way. I argue that information-processing mechanisms are indispensable in explanations of cognitive phenomena, and this vindicates the computational explanation of cognition. At the same time, (...) it has to be supplemented with other explanations to make the mechanistic explanation complete, and that naturally leads to explanatory pluralism in cognitive science. The price to pay for pluralism, however, is the abandonment of the traditional autonomy thesis asserting that cognition is independent of implementation details. (shrink)
Recent research in computational neuroscience has demonstrated that we now possess the ability to simulate neural systems in significant detail and on a large scale. Simulations on the scale of a human brain have recently been reported. The ability to simulate entire brains (or significant portions thereof) would be a revolutionary scientific advance, with substantial benefits for brain science. However, the prospect of whole-brain simulation comes with a set of new and unique ethical questions. In the present paper, we (...) briefly outline certain of those problems and emphasize the need to begin considering the ethical aspects of computational neuroscience. (shrink)
In light of the sharp linguistic turn philosophy has taken in this century, this collection provides a much-needed and long-overdue reference for philosophical discussion. The first collection of its kind, it explores questions of the nature and existence of linguistic objects--including sentences and meanings--and considers the concept of truth in linguistics. The status of linguistics and the nature of language now take a central place in discussions of the nature of philosophy; the essays in this volume both inform (...) these discussions and lay the groundwork for further examination. (shrink)
Most previous works on responsible conduct of research have focused on good practices in laboratory experiments. Because computation now rivals experimentation as a mode of scientific research, we sought to identify the responsibilities of researchers who develop or use computational modeling and simulation. We interviewed nineteen experts to collect examples of ethical issues from their experiences in conducting research with computational models. We gathered their recommendations for guidelines for computational research. Informed by these interviews, we describe the (...) respective professional responsibilities of developers and users of computational models in research. In particular, we examine whether developers should disclose the full computational codes, and we explain how developers and users should minimize harms from improper uses of models. (shrink)
As hopes that generative linguistics might solve philosophical problems about the mind give way to disillusionment, old problems concerning the relationship between linguistics and philosophy survive unresolved. This collection surveys the historical engagement between the two, and opens up avenues for further reflection. In Part 1 two contrasting views are presented of the interface nowadays called 'philosophy of linguistics'. Part 2 gives a detailed historical survey of the engagement of analytic philosophy with linguistic problems during the present (...) century, and sees the imposition by philosophers of an 'exploratory' model of thinking as a major challenge to the discipline of linguistics. Part 3 poses the problem of whether linguistics is dedicated to describing independently existing linguistic structures or to imposing its own structures on linguistic phenomena. In Part 4 Harris points out some similarities in the way an eminent linguist and an eminent philosopher invoke the analogy between languages and games; while Taylor analyses the rationale of our metalinguistic claims and their relationship to linguistic theorizing. Providing a wide range of views and ideas this book will be of interest to all those interested and involved in the interface of philosophy and linguistics. (shrink)
Recent findings indicate that the constituting digits of multi-digit numbers are processed, decomposed into units, tens, and so on, rather than integrated into one entity. This is suggested by interfering effects of unit digit processing on two-digit number comparison. In the present study, we extended the computational model for two-digit number magnitude comparison of Moeller, Huber, Nuerk, and Willmes (2011a) to the case of three-digit number comparison (e.g., 371_826). In a second step, we evaluated how hundred-decade and hundred-unit compatibility (...) effects were moderated by varying the percentage of within-hundred (e.g., 539_582) and within-hundred-and-decade filler items (e.g., 483_489). From the results we predict that numerical distance as well as compatibility effects should indeed be modulated by the relevance of tens and units in three-digit number magnitude comparison: While in particular the hundred distance effect should decrease, we predict hundred-decade and hundred-unit compatibility effects to increase with the relevance of tens and units. (shrink)
Authoritative and wide-ranging, this book examines the history of western linguistics over a 2000-year timespan, from its origins in ancient Greece up to the crucial moment of change in the Renaissance that laid the foundations of modern linguistics. Some of today's burning questions about language date back a long way: in 1400 BC Plato was asking how words relate to reality. Other questions go back just a few generations, such as our interest in the mechanisms of language change, (...) or in the social factors that shape the way we speak. Vivien Law explores how ideas about language over the centuries have changed to reflect changing modes of thinking. A survey chapter brings the coverage of the book up to the present day. Classified bibliographies and chapters on research resources and the qualities the historian of linguistics needs to develop, provide the reader with the tools to go further. (shrink)
The primary goal of this essay is to demonstrate how considerations from computational complexity theory can inform grammatical theorizing. To this end, generalized phrase structure grammar (GPSG) linguistic theory is revised so that its power more closely matches the limited ability of an ideal speaker-hearer: GPSG Recognition is EXP-POLY time hard, while Revised GPSG Recognition is NP-complete. A second goal is to provide a theoretical framework within which to better understand the wide range of existing GPSG models, embodied in (...) formal definitions as well as in implemented computer programs. (shrink)
Computational sociology models social phenomena using the concepts of emergence and downward causation. However, the theoretical status of these concepts is ambiguous; they suppose too much ontology and are invoked by two opposed sociological interpretations of social reality: the individualistic and the holistic. This paper aims to clarify those concepts and argue in favour of their heuristic value for social simulation. It does so by proposing a link between the concept of emergence and Luhmann's theory of communication. For Luhmann, (...) society emerges from the bottom-up as communication and he describes the process by which society limits the possible selections of individuals as downward causation. It is argued that this theory is well positioned to overcome some epistemological drawbacks in computational sociology. (shrink)
In recent works, Chomsky has once more endorsed a computational view of rulefollowing, whereby to follow a rule is to operate certain computations on a subject’s mental representations. As is well known, this picture does not conform to what we may call the grammatical conception of rule-following outlined by Wittgenstein, whereby an elucidation of the concept of rule-following is aimed at by isolating grammatical statements regarding the phrase ‘to follow a rule’. As a result, Chomskyan and Wittgensteinian treatments of (...) topics immediately connected with rule-following, namely linguistic competence and understanding, are utterly different from one another. There are two possible stances that computationalists like Chomsky may adopt with regard to the discrepancy between the two aforementioned modes of dealing with rule-following, namely a conciliatory and a non-conciliatory attitude. According to the former attitude, grammatical remarks on and computationallyoriented theories of rule-following investigate one and the same topic although admittedly at different levels, namely a conceptual and an empirical one. According to the latter attitude, grammatical remarks are just a preliminary step in the investigation of rule-following which scientific advancement, presently represented by computationally-oriented theories on this matter, is well entitled to put aside. In what follows, however, I will try to show that both stances are problematic. The conciliatory attitude simply does not work, for it hardly copes with the fact that the concept of rule-following does not supervene, even weakly, on the property of rule-following, namely the property instantiated in the mental/cerebral phenomena that computationally-oriented theories of rule-following study. To take the contrary attitude, on the other hand, is to end up with another disappointing result, namely that the computational treatment of rule-following ultimately deals with something different from that which we wished to gain knowledge of when we began our inquiry into rule-following.. (shrink)
Abstract This paper explains how mathematical computation can be constructed from weaker recursive patterns typical of natural languages. A thought experiment is used to describe the formalization of computational rules, or arithmetical axioms, using only orally-based natural language capabilities, and motivated by two accomplishments of ancient Indian mathematics and linguistics. One accomplishment is the expression of positional value using versified Sanskrit number words in addition to orthodox inscribed numerals. The second is Panini’s invention, around<br>the fifth century BCE, of (...) a formal grammar for spoken Sanskrit, expressed in oral verse extending ordinary Sanskrit, and using recursive methods rediscovered in the twentieth century. The Sanskrit positional number compounds and Panini’s formal system are construed as linguistic grammaticalizations relying on tacit cognitive models of symbolic form. The thought experiment shows that universal computation can be constructed from natural language structure and skills, and shows why intentional capabilities needed for language use play a role in computation across all<br>media. The evolution of writing and positional number systems in Mesopotamia is used to transfer the thought experiment of “oral arithmetic” to inscribed computation. The thought experiment and historical evidence combine to show how and why mathematical computation is a cognitive technology extending generic symbolic skills associated with language structure, usage, and change. (shrink)
The International workshop 'Frontiers of Combining Systems' is the only forum that is exclusively devoted to research efforts in this interdisciplinary area. This volume contains selected, edited papers from the second installment of the workshop. The contributions range from theorem proving, rewriting and logic to systems and constraints. While there is a clear emphasis on automated tools and logics, the contributions to this volume show that there exists a rapidly expanding body of solutions of particular instances of the combination problem, (...) and at the same time, that the issue of developing general frameworks for intergrating formalisms and systems is taking on an increasingly important position on the international research agenda. The idea of combining formal systems and algorithms has been attracting interest in areas as diverse as constraint logic programming, automated deduction, verification, information retrieval, computationallinguistics, artificial intelligence, and logic. As any interesting real world system is a complex composite entity, decomposing its descriptive requirements (for design, verification, or maintenance purposes) into simpler, more restricted tasks is appealing as it is often the only plausible way of tackling complex modelling problems. A core body of notions, questions and results is beginning to emerge in the area, and we are beginning to understand the computational and logical impact of combining methods and algorithms. (shrink)
There were in the past, just as there are in the present, several diverse attempts to establish a unique theory capable of identifying in all natural languages a similar, invariable basic structure of a logical nature. If such a theory exists, then there must be principles that rule the functioning of these languages and they must have a logical origin. Based on a work by the French linguist, Oswald Ducrot, entitled D’un mauvais usage de la logique , this paper aims (...) to present in a concise manner two of the above mentioned attempts. They were elaborated in diverse epochs and different arguments were put forward to support them. The first attempt was in XVII century France and its theoretic basis was the renowned ‘Port-Royal Logic’. The second attempt is recent and its theoretic support comes from Contemporary Logic. DOI: 10.5007/1808-1711.2011v15n1p111. (shrink)
After reviewing some major features of theinteractions between Linguistics and Philosophyin recent years, I suggest that the depth and breadthof current inquiry into semanticshas brought this subject into contact both with questionsof the nature of linguistic competence and with modern andtraditional philosophical study of the nature ofour thoughts, and the problems of metaphysics.I see this development as promising for thefuture of both subjects.
Semantics is concerned with meaning: what meanings are, how meanings are assigned to words, phrases and sentences of natural and formal languages, and how meanings can be combined and used for inference and reasoning. The goal of this chapter is to introduce computational linguists and computer scientists to the tools, methods, and concepts required to work on natural language semantics. Semantics, while often paired with pragmatics, is nominally distinct. On a traditional view, semantics concerns itself with the compositional buildup (...) of meaning from the lexicon to the sentence level whereas pragmatics concerns the way in which contextual factors and speaker intentions affect meaning and inference (see, e.g., Potts to appear in this volume). Although the semantics-pragmatics distinction is historically important, and continues to be widely adopted, in practice it is not clearcut. Work in semantics inevitably involves pragmatics and vice versa. Furthermore, it is not a distinction which is of much relevance for applications in computationallinguistics. This chapter is organized as follows. In sections 2 and 3 we introduce foundational concepts and discuss ways of representing the meaning of sentences, and of combining the meaning of smaller expressions to produce those sentential meanings. In section 4 we discuss the representation of meaning for larger units, especially with respect to anaphora, and introduce two formal theories that go beyond sentence meaning: Discourse Representation Theory and Dynamic Semantics. Then, in section 5 we discuss temporality, introducing event semantics, and describing standard approaches to the semantics of tense and aspect. Section 6 concerns the tension between the surface-oriented statistical methods characteristic of much of computationallinguistics and the more abstract methods typical of formal semantics and includes discussion of a range of phenomena for which it seems particularly important to utilize insights from formal semantics.. (shrink)
This paper investigates the issue whether metaphors have a metaphorical or secondary meaning and how this question is related to the borderline between philosophy and linguistics. On examples by V. Woolf and H. W. Auden, it will be shown that metaphor accomplishes something more than its literal meaning expresses and this “more” cannot be captured by any secondary meaning. What is essential in the metaphor is not a secondary meaning but an internal relation between a metaphorical proposition and a (...) description of its effects. In order to understand metaphors, we have to share an ability to construe metaphorical meanings at once. The aim of this ability is to uncover an internal relation, which lies behind a particular metaphor. (shrink)
Inspired by the success of generative linguistics and transformational grammar, proponents of the linguistic analogy (LA) in moral psychology hypothesize that careful attention to folk-moral judgments is likely to reveal a small set of implicit rules and structures responsible for the ubiquitous and apparently unbounded capacity for making moral judgments. As a theoretical hypothesis, LA thus requires a rich description of the computational structures that underlie mature moral judgments, an account of the acquisition and development of these structures, (...) and an analysis of those components of the moral system that are uniquely human and uniquely moral. In this paper we present the theoretical motivations for adopting LA in the study of moral cognition: (a) the distinction between competence and performance, (b) poverty of stimulus considerations, and (c) adopting the computational level as the proper level of analysis for the empirical study of moral judgment. With these motivations in hand, we review recent empirical findings that have been inspired by LA and which provide evidence for at least two predictions of LA: (a) the computational processes responsible for folk-moral judgment operate over structured representations of actions and events, as well as coding for features of agency and outcomes; and (b) folk-moral judgments are the output of a dedicated moral faculty and are largely immune to the effects of context. In addition, we highlight the complexity of the interfaces between the moral faculty and other cognitive systems external to it (e.g., number systems). We conclude by reviewing the potential utility of the theoretical and empirical tools of LA for future research in moral psychology. (shrink)
Methodological questions concerning Chomsky’s generative approach to linguistics have been debated without consensus. The status of linguistics as psychology, the psychological reality of grammars, the character of tacit knowledge and the role of intuitions as data remain heatedly disputed today. I argue that the recalcitrance of these disputes is symptomatic of deep misunderstandings. I focus attention on Michael Devitt’s recent extended critique of Chomskyan linguistics and I suggest that his complaints are based on a failure to appreciate (...) the special status of Chomsky’s computational formalisms found elsewhere in cognitive science. Devitt ascribes an intentional conception of representations that Chomsky repudiates and that is independently implausible. I argue that Devitt’s proposed “linguistic reality” as the proper subject matter of linguistics neglects the problems of tokens as opposed to types and he misses the force of Chomsky’s arguments against Behaviourism and nominalism. I suggest that Devitt’s case against intuitions as data misunderstands their standard role throughout perceptual psychology. Finally, of more general interest, I argue that Devitt’s position exemplifies compelling errors concerning mental representation seen throughout cognitive science and philosophy of mind. (shrink)
Lexical ambiguity presents one of the most intractable problems for language processing studies and, not surprisingly, it is at the core of research in lexical semantics. Originally published as two special issues of the Journal of Semantics, this collection focuses on the problem of polysemy, from the point of view of practitioners of computationallinguistics.
A key topic in the work of Burghard Rieger is the notion of meaning. To explore this notion, he and his collaborators developed a most sophisticated approach combining theoretical ideas and concepts of semiotics with empirical and numerical tools of computationallinguistics (see [31] for a most recent comprehensive account). In the present contribution, relations of Rieger’s achievements to some issues of interest in the physics and philosophy of complex systems will be addressed.
Situation theory has been developed over the last decade and various versions of the theory have been applied to a number of linguistic issues. However, not much work has been done in regard to its computational aspects. In this paper, we review the existing approaches towards `computational situation theory' with considerable emphasis on our own research.
This book provides a systematic study of three foundational issues in the semantics of natural language that have been relatively neglected in the past few decades. focuses on the formal characterization of intensions, the nature of an adequate type system for natural language semantics, and the formal power of the semantic representation language proposes a theory that offers a promising framework for developing a computational semantic system sufficiently expressive to capture the properties of natural language meaning while remaining computationally (...) tractable written by two leading researchers and of interest to students and researchers in formal semantics, computationallinguistics, logic, artificial intelligence, and the philosophy of language. (shrink)
In this paper I introduce a formalism for natural language understandingbased on a computational implementation of Discourse RepresentationTheory. The formalism covers a wide variety of semantic phenomena(including scope and lexical ambiguities, anaphora and presupposition),is computationally attractive, and has a genuine inference component. Itcombines a well-established linguistic formalism (DRT) with advancedtechniques to deal with ambiguity (underspecification), and isinnovative in the use of first-order theorem proving techniques.The architecture of the formalism for natural language understandingthat I advocate consists of three levels of (...) processing:underspecification, resolution, andinference. Each of these levels has a distinct function andtherefore employs a different kind of semantic representation. Themappings between these different representations define the interfacesbetween the levels. (shrink)
This project continues our interdisciplinary research into computational and cognitive aspects of narrative comprehension. Our ultimate goal is the development of a computational theory of how humans understand narrative texts. The theory will be informed by joint research from the viewpoints of linguistics, cognitive psychology, the study of language acquisition, literary theory, geography, philosophy, and artificial intelligence. The linguists, literary theorists, and geographers in our group are developing theories of narrative language and spatial understanding that are being (...) tested by the cognitive psychologists and language researchers in our group, and a computational model of a reader of narrative text is being developed by the AI researchers, based in part on these theories and results and in part on research on knowledge representation and reasoning. This proposal describes the knowledge-representation and natural-language-processing issues involved in the computational implementation of the theory; discusses a contrast between communicative and narrative uses of language and of the relation of the narrative text to the story world it describes; investigates linguistic, literary, and hermeneutic dimensions of our research; presents a computational investigation of subjective sentences and reference in narrative; studies children’s acquisition of the ability to take third-person perspective in their own storytelling; describes the psychological validation of various linguistic devices; and examines how readers develop an understanding of the geographical space of a story. This report is a longer version of a project description submitted to NSF. This document, produced in May 2007, is a L ATEX version of Technical Report 89-07 (Buffalo: SUNY Buffalo Department of Computer Science, August 1989), with slightly.. (shrink)
Language understanding is one of the most important characteristics for human beings. As a pervasive phenomenon in natural language, metaphor is not only an essential thinking approach, but also an ingredient in human conceptual system. Many of our ways of thinking and experiences are virtually represented metaphorically. With the development of the cognitive research on metaphor, it is urgent to formulate a computational model for metaphor understanding based on the cognitive mechanism, especially with the view to promoting natural language (...) understanding. Many works have been done in pragmatics and cognitive linguistics, especially the discussions on metaphor understanding process in pragmatics and metaphor mapping representation in cognitive linguistics. In this paper, a theoretical framework for metaphor understanding based on the embodied mechanism of concept inquiry is proposed. Based on this framework, ontology is introduced as the knowledge representation method in metaphor understanding, and metaphor mapping is formulated as ontology mapping. In line with the conceptual blending theory, a revised conceptual blending framework is presented by adding a lexical ontology and context as the fifth mental space, and a metaphor mapping algorithm is proposed. (shrink)
previous theories and the relevance of those criticisms to the new accounts. Additionally, we have included a new section at the end, which gives some directions to literature outside of formal semantics in which the notion of mass has been employed. We looked at work on mass expressions in psycholinguistics and computationallinguistics here, and we discussed some research in the history of philosophy and in metaphysics that makes use of the notion of mass.
The beginning of this century hailed a new paradigm in linguistics, the paradigm brought about by de Saussure's Cours de Linguistique Genérále and subsequently elaborated by Jakobson, Hjelmslev and other linguists. It seemed that the linguistics of this century was destined to be structuralistic. However, half of the century later a brand new paradigm was introduced by Chomsky's Syntactic Structures followed by Montague's formalization of semantics. This new turn has brought linguistics surprisingly close to mathematics and logic, (...) and has facilitated a direct practical exploitation of linguistic theory by computer science. (shrink)
In this paper, we explore the possibility that machine learning approaches to naturallanguage processing being developed in engineering-oriented computationallinguistics may be able to provide specific scientific insights into the nature of human language. We argue that, in principle, machine learning results could inform basic debates about language, in one area at least, and that in practice, existing results may offer initial tentative support for this prospect. Further, results from computational learning theory can inform arguments carried on (...) within linguistic theory as well. (shrink)
This book asks not only how the study of white-collar crime can enrich our understanding of crime and justice more generally, but also how criminological ...
The “surge in use of finite-state methods” ([10]) in computationallinguistics has largely, if not completely, left semantics untouched. The present paper is directed towards correcting this situation. Techniques explained in [1] are applied to a fragment of temporal semantics through an approach we call finite-state temporality. This proceeds from the intuition of an event as “a series of snapshots” ([15]; see also [12]), equating snapshots with symbols that collectively form our alphabet. A sequence of snapshots then becomes (...) a string over that alphabet, evoking comic/film strips. Jackendoff has, among others, objected to conceptualizing events in terms of snapshots ([8]). To counter these objections, we step up from events-as-strings to event-typesas-regular languages ([5, 6]), recognizing the need for variable granularity. Beyond the introduction of disjunction implicit in the step from a single string up to a set of strings, we obtain a useful logic from the regular operations and a careful choice of the snapshots (constituting our alphabet). (shrink)
Computational learning theory explores the limits of learnability. Studying language acquisition from this perspective involves identifying classes of languages that are learnable from the available data, within the limits of time and computational resources available to the learner. Different models of learning can yield radically different learnability results, where these depend on the assumptions of the model about the nature of the learning process, and the data, time, and resources that learners have access to. To the extent that (...) such assumptions accurately reflect human language learning, a model that invokes them can offer important insights into the formal properties of natural languages, and the way in which their representations might be efficiently acquired. In this chapter we consider several computational learning models that have been applied to the language learning task. Some of these have yielded results that suggest that the class of natural languages cannot be efficiently learned from the primary linguistic data (PLD) available to children, through.. (shrink)
For any extension $T$ of $I\Sigma_{1}$ having a cut-elimination property extending that of $I\Sigma_{1}$ , the number of different proofs that can be obtained by cut elimination from a single $T$ -proof cannot be bound by a function which is provably total in $T$.
