Results for 'Natural language'

1000+ found
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  1. Natural Language and Natural Selection.Steven Pinker & Paul Bloom - 1990 - Behavioral and Brain Sciences 13 (4):707-27.
    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 (...)
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  2.  69
    Ethical Pitfalls for Natural Language Processing in Psychology.Mark Alfano, Emily Sullivan & Amir Ebrahimi Fard - forthcoming - In Morteza Dehghani & Ryan Boyd (eds.), The Atlas of Language Analysis in Psychology. Guilford Press.
    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 (...)
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  3.  32
    Levels of Ontology and Natural Language: The Case of the Ontology of Parts and Wholes.Friederike Moltmann - forthcoming - In James Miller (ed.), The Language of Ontology. Oxford University Press.
    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 (...)
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  4.  56
    Natural Language Ontology (Routledge Handbook of Metametaphysics).Friederike Moltmann - forthcoming - In Ricki Bliss & James Miller (eds.), The Routledge Handbook of Metametaphysics. Routledge.
    This paper gives an outline of natural language ontology as a subdiscipline of both linguistics and philosophy. It argues that part of the constructional ontology reflected in natural language is in significant respects on a par with syntax (on the generative view).
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  5. Proof-Theoretic Semantics for a Natural Language Fragment.Nissim Francez & Roy Dyckhoff - 2010 - Linguistics and Philosophy 33 (6):447-477.
    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 (...)
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  6. Logical Consequence and Natural Language.Michael Glanzberg - 2015 - In Colin Caret & Ole Hjortland (eds.), Foundations of Logical Consequence. Oxford University Press. pp. 71-120.
    One of the great successes in the study of language has been the application of formal methods, including those of formal logic. Even so, this chapter argues against one way of accounting for this success, by arguing that the study of natural language semantics and of logical consequence relations are not the same. There is indeed a lot we can glean about logic from looking at our languages, and at our inferential practices, but the semantic properties of (...)
     
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  7. Natural Language Ontology.Friederike Moltmann - 2017 - Oxford Encyclopedia of Linguistics.
    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 (...) language ontology is important, and what may be distinctive of the ontological categories and structures reflected in natural language. (shrink)
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  8.  52
    Natural Language Inference in Coq.Stergios Chatzikyriakidis & Zhaohui Luo - 2014 - Journal of Logic, Language and Information 23 (4):441-480.
    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 (...)
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  9. Abstract Objects and the Core-Periphery Distinction in the Ontological and the Conceptual Domain of Natural Language.Friederike Moltmann - forthcoming - In José Luis Falguera & María De La Martínez Vidal (eds.), Abstract Objects: For and Against. Springer.
    This paper elaborates distinctions between a core and a periphery in the ontological and the conceptual domain associated with natural language. The ontological core-periphery distinction is essential for natural language ontology and is the basis for the central thesis of my 2013 book Abstract Objects and the Semantics of Natural Language, namely that natural language permits reference to abstract objects in its periphery, but not its core.
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  10.  25
    Natural Language and Logic of Agency.Johan van Benthem - 2014 - Journal of Logic, Language and Information 23 (3):367-382.
    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.
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  11.  31
    Towards a Natural Language Semantics Without Functors and Operands.Miklós Erdélyi-Szabó, László Kálmán & Agi Kurucz - 2008 - Journal of Logic, Language and Information 17 (1):1-17.
    The paper sets out to offer an alternative to the function/argument approach to the most essential aspects of natural language meanings. That is, we question the assumption that semantic completeness (of, e.g., propositions) or incompleteness (of, e.g., predicates) exactly replicate the corresponding grammatical concepts (of, e.g., sentences and verbs, respectively). We argue that even if one gives up this assumption, it is still possible to keep the compositionality of the semantic interpretation of simple predicate/argument structures. In our opinion, (...)
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  12. Natural Language Understanding: Methodological Conceptualization.Vitalii Shymko - 2019 - Psycholinguistics 25 (1):431-443.
    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 (...)
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  13. Inner Speech, Natural Language, and the Modularity of the Mind.Axel Gelfert - 2015 - Kairos 14 (1):7-29.
    Inner speech is a pervasive feature of our conscious mental lives. Yet its function and character remain an issue of philosophical debate. The present paper focuses on the relation between inner speech and natural language and on the cognitive functions that various contributors have ascribed to inner speech. In particular, it is argued that inner speech does not consist of bare, context-free internal presentations of sentential (or subsentential) content, but rather has an ineliminably perspectival element. The proposed model (...)
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  14. A MODERN SCIENTIFIC INSIGHT OF SPHOTA VADA: IMPLICATIONS TO THE DEVELOPMENT OF SOFTWARE FOR MODELING NATURAL LANGUAGE COMPREHENSION.Varanasi Ramabrahmam - manuscript
    Sabdabrahma Siddhanta, popularized by Patanjali and Bhartruhari will be scientifically analyzed. Sphota Vada, proposed and nurtured by the Sanskrit grammarians will be interpreted from modern physics and communication engineering points of view. Insight about the theory of language and modes of language acquisition and communication available in the Brahma Kanda of Vakyapadeeyam will be translated into modern computational terms. A flowchart of language processing in humans will be given. A gross model of human language acquisition, comprehension (...)
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  15.  14
    Idealisation in Natural Language Semantics: Truth-Conditions for Radical Contextualists.Gabe Dupre - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of (...)
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  16. Natural Language and its Ontology.Friederike Moltmann - 2019 - In Alvin Goldman & Brian Mclaughlin (eds.), Metaphysics and Cognitive Science. Oxford: Oxford University Press. pp. 206-232.
    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.
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  17. THE PHYSICAL STRUCTURE AND FUNCTION OF MIND: A MODERN SCIENTIFIC TRANSLATION OF ADVAITA PHILOSOPHY WITH IMPLICATIONS AND APPLICATION TO COGNITIVE SCIENCES AND NATURAL LANGUAGE COMPREHENSION.Varanasi Ramabrahmam - 2008 - In Proceedings of the national seminar on Sanskrit in the Modern Context conducted by Department of Sanskrit Studies and the School of humanities, University of Hyderabad between11-13, February 2008.
    The famous advaitic expressions -/- Brahma sat jagat mithya jivo brahma eva na apraha and Asti bhaati priyam namam roopamcheti amsa panchakam AAdya trayam brahma roopam tato dwayam jagat roopam -/- will be analyzed through physics and electronics and interpreted. -/- Four phases of mind, four modes of language acquisition and communication and seven cognitive states of mind participating in human cognitive and language acquisition and communication processes will be identified and discussed. -/- Implications and application of such (...)
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  18. Indefinite Extensibility in Natural Language.Laureano Luna - 2013 - The Monist 96 (2):295-308.
    The Monist’s call for papers for this issue ended: “if formalism is true, then it must be possible in principle to mechanize meaning in a conscious thinking and language-using machine; if intentionalism is true, no such project is intelligible”. We use the Grelling-Nelson paradox to show that natural language is indefinitely extensible, which has two important consequences: it cannot be formalized and model theoretic semantics, standard for formal languages, is not suitable for it. We also point out (...)
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  19. Ontology-Assisted Database Integration to Support Natural Language Processing and Biomedical Data-Mining.Jean-Luc Verschelde, Marianna C. Santos, Tom Deray, Barry Smith & Werner Ceusters - 2004 - Journal of Integrative Bioinformatics. Repr. In: Yearbook of Bioinformatics , 39–48 1:1-10.
    Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for the purposes of (...)
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  20. The Language of Thought and Natural Language Understanding.Jonathan Knowles - 1998 - Analysis 58 (4):264-272.
    Stephen Laurence and Eric Margolis have recently argued that certain kinds of regress arguments against the language of thought (LOT) hypothesis as an account of how we understand natural languages have been answered incorrectly or inadequately by supporters of LOT ('Regress arguments against the language of thought', Analysis, 57 (1), 60-6, J 97). They argue further that this does not undermine the LOT hypothesis, since the main sources of support for LOT are (or might be) independent of (...)
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  21.  13
    Translating a Fragment of Natural Deduction System for Natural Language Into Modern Type Theory.Ivo Pezlar - 2019 - In Rainer Osswald, Christian Retoré & Peter Sutton (eds.), Proceedings of the IWCS 2019 Workshop on Computing Semantics with Types, Frames and Related Structures. Stroudsburg, PA: Association for Computational Linguistics. pp. 10-18.
    In this paper, we investigate the possibility of translating a fragment of natural deduction system (NDS) for natural language semantics into modern type theory (MTT), originally suggested by Luo (2014). Our main goal will be to examine and translate the basic rules of NDS (namely, meta-rules, structural rules, identity rules, noun rules and rules for intersective and subsective adjectives) to MTT. Additionally, we will also consider some of their general features.
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  22. Boguslawski's Analysis of Quantification in Natural Language.John-Michael Kuczynski - 2010 - Journal of Pragmatics 42 (10):2836-2844.
    The semantic rules governing natural language quantifiers (e.g. "all," "some," "most") neither coincide with nor resemble the semantic rules governing the analogues of those expressions that occur in the artificial languages used by semanticists. Some semanticists, e.g. Peter Strawson, have put forth data-consistent hypotheses as to the identities of the semantic rules governing some natural-language quantifiers. But, despite their obvious merits, those hypotheses have been universally rejected. In this paper, it is shown that those hypotheses are (...)
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  23. Formal Semantics of Natural Language[REVIEW]Adam Morton - 1982 - Canadian Journal of Philosophy 12 (4):805-808.
    a review of Keenan, ed. *Formal Semantics of Natural Language*.
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  24.  86
    An Expressive First-Order Logic with Flexible Typing for Natural Language Semantics.Chris Fox & Shalom Lappin - 2004 - Logic Journal of the Interest Group in Pure and Applied Logics 12 (2):135--168.
    We present Property Theory with Curry Typing (PTCT), an intensional first-order logic for natural language semantics. PTCT permits fine-grained specifications of meaning. It also supports polymorphic types and separation types. 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 type-theoretic approach to pronominal anaphora that avoids some of the difficulties that undermine (...)
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  25.  77
    Natural Language Processing Using a Propositional Semantic Network with Structured Variables.Syed S. Ali & Stuart C. Shapiro - 1993 - Minds and Machines 3 (4):421-451.
    We describe a knowledge representation and inference formalism, based on an intensional propositional semantic network, in which variables are structures terms consisting of quantifier, type, and other information. This has three important consequences for natural language processing. First, this leads to an extended, more natural formalism whose use and representations are consistent with the use of variables in natural language in two ways: the structure of representations mirrors the structure of the language and allows (...)
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  26.  84
    Some Comments on the Begriffsschrift and Natural Language.Alan Schwerin - 1983 - Philosophical Papers 12 (2):32-38.
    If the begriffsschrift from Frege does represent the logical form of natural language it either lacks a logical form itself, or its logical form is different to that of natural language. But Frege insists that his notation has a logical form. So the second disjunct holds. This suggests that Frege's notation will generate consequences different to those that can be derived with natural language, with its different logical form. For anyone looking for "a means (...)
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  27.  26
    Natural Language Interfaces and Strategic Computing.Geoffrey K. Pullum - 1987 - AI and Society 1 (1):47-58.
    Modern weaponry is often too complex for unaided human operation, and is largely or totally controlled by computers. But modern software, particularly artificial intelligence software, exhibits such complexity and inscrutability that there are grave dangers associated with its use in non-benign applications. Recent efforts to make computer systems more accessible to military personnel through natural language processing systems, as proposed in the Strategic Computing Initiative of the Defense Advanced Research Projects Agency, increases rather than decreases the dangers of (...)
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  28.  58
    Logical Reasoning in Natural Language: It is All About Knowledge. [REVIEW]Lucja Iwańska - 1993 - Minds and Machines 3 (4):475-510.
    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 (...)
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  29.  19
    Incremental Bayesian Category Learning From Natural Language.Lea Frermann & Mirella Lapata - 2016 - Cognitive Science 40 (6):1333-1381.
    Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words. We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: the acquisition of features that discriminate among categories, and the grouping of concepts into categories based on (...)
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  30.  47
    Natural Language Processing for Transparent Communication Between Public Administration and Citizens.Bernardo Magnini, Elena Not, Oliviero Stock & Carlo Strapparava - 2000 - Artificial Intelligence and Law 8 (1):1-34.
    This paper presents two projects concerned with the application of natural language processing technology for improving communication between Public Administration and citizens. The first project, GIST,is concerned with automatic multilingual generation of instructional texts for form-filling. The second project, TAMIC, aims at providing an interface for interactive access to information, centered on natural language processing and supposed to be used by the clerk but with the active participation of the citizen.
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  31.  27
    Natural Language Understanding Within a Cognitive Semantics Framework.Inger Lytje - 1989 - AI and Society 4 (4):276-290.
    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.
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  32.  17
    Prior and Temporal Sequences for Natural Language.Tim Fernando - 2016 - Synthese 193 (11).
    Logics of discrete time are, in Arthur Prior’s words, “applicable in limited fields of discourse in which we are concerned with what happens in a sequence of discrete states,” independent of “any serious metaphysical assumption that time is discrete.” This insight is applied to natural language semantics, a widespread assumption in which is that time is, as is the real line, dense. “Limited fields of discourse” are construed as finite sets of temporal propositions, inducing bounded notions of temporal (...)
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  33. Representing Time in Natural Language the Dynamic Interpretation of Tense and Aspect.Alice G. B. ter Meulen - 1997
     
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  34. Modularity in Knowledge Representation and Natural-Language Understanding.Jay L. Garfield (ed.) - 1987 - MIT Press.
  35. Natural Language and Everyday Reasoning.Fred Sommers - manuscript
  36. Understanding Natural Language.John Haugeland - 1979 - Journal of Philosophy 76 (November):619-32.
  37. Deontic Logic and Natural Language.Fabrizio Cariani - forthcoming - In Dov Gabbay, Ron van der Meyden, John Horty, Xavier Parent & Leandert van der Torre (eds.), The Handbook of Deontic Logic (Vol. II). College Publications.
    There has been a recent surge of work on deontic modality within philosophy of language. This work has put the deontic logic tradition in contact with natural language semantics, resulting in significant increase in sophistication on both ends. This chapter surveys the main motivations, achievements, and prospects of this work.
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  38. Natural Language and Thought: Thinking in English.Barbara Abbott - 1995 - Behavior and Philosophy 23 (2):49-55.
  39.  6
    Natural Language Dialog with a Tutor System for Mathematical Proofs.Christoph Benzmüller, Helmut Horacek, Ivana Kruijff-Korbayova, Manfred Pinkal, Jörg Siekmann & Magdalena Wolska - 2007 - In Ruqian Lu, Jörg Siekmann & Carsten Ullrich (eds.), Cognitive Systems. Springer. pp. 1-14.
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  40. Symbolic Connectionism in Natural Language Disambiguation.James Franklin & S. W. K. Chan - 1998 - IEEE Transactions on Neural Networks 9:739-755.
    Uses connectionism (neural networks) to extract the "gist" of a story in order to represent a context going forward for the disambiguation of incoming words as a text is processed.
     
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  41.  9
    Forgetting and Natural Language Mediation.William E. Montague, Jack A. Adams & Harold O. Kiess - 1966 - Journal of Experimental Psychology 72 (6):829.
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  42. Natural Language and Thought: Doing Without Mentalese.Larry Hauser - 1995 - Behavior and Philosophy 23 (2):41-47.
    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.
     
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  43.  4
    Effects of Natural Language Mediators on Short-Term Memory.Harold O. Kiess - 1968 - Journal of Experimental Psychology 77 (1):7.
  44.  11
    Item Length, Acoustic Similarity, and Natural Language Mediation as Variables in Short-Term Memory.Jack A. Adams, Howard I. Thorsheim & John S. McIntyre - 1969 - Journal of Experimental Psychology 80 (1):39.
  45.  7
    Natural Language Associability in Paired-Associate Learning.Clinton B. Walker, William E. Montague & Alexander J. Wearing - 1970 - Journal of Experimental Psychology 84 (2):264.
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  46. Natural Language Understanding and Logic Programming, Ii Proceedings of the Second International Workshop on Natural Language Understanding and Logic Programming, Vancouver, Canada, 17-19 August, 1987. [REVIEW]Veronica Dahl & Patrick Saint-Dizier - 1988
     
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  47.  33
    The Semantic Representation of Natural Language.Michael Levison - 2012 - Bloomsbury Academic.
    Introduction -- Basic concepts -- Previous approaches -- Semantic expressions: introduction -- Formal issues -- Semantic expressions: basic features -- Advanced features -- Applications: capture -- Three little pigs -- Applications: creation.
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  48. From Natural Language Processing to Logic for Expert Systems a Logic Based Approach to Artificial Intelligence.André Thayse & Jean-Louis Binot - 1991
  49. A Meeting of the Conceptual and the Natural: Wittgenstein on Learning a Sensation‐Language.Hao Tang - 2015 - Philosophy and Phenomenological Research 91 (1):105-135.
    Since the rise of modern natural science there has been deep tension between the conceptual and the natural. Wittgenstein's discussion of how we learn a sensation-language contains important resources that can help us relieve this tension. The key here, I propose, is to focus our attention on animal nature, conceived as partially re-enchanted. To see how nature, so conceived, helps us relieve the tension in question, it is crucial to gain a firm and detailed appreciation of how (...)
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  50. Abstract Objects and the Semantics of Natural Language.Friederike Moltmann - 2013 - Oxford University Press.
    This book pursues the question of how and whether natural language allows for reference to abstract objects in a fully systematic way. By making full use of contemporary linguistic semantics, it presents a much greater range of linguistic generalizations than has previously been taken into consideration in philosophical discussions, and it argues for an ontological picture is very different from that generally taken for granted by philosophers and semanticists alike. Reference to abstract objects such as properties, numbers, propositions, (...)
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