Computational models of semantic memory exploit information about co-occurrences of words in naturally occurring text to extract information about the meaning of the words that are present in the language. Such models implicitly specify a representation of temporal context. Depending on the model, words are said to have occurred in the same context if they are presented within a moving window, within the same sentence, or within the same document. The temporal context model (TCM), which specifies a particular definition (...) of temporal context, has proved useful in the study of episodic memory. The predictive temporal context model (pTCM) uses the same definition of temporal context to generate semantic memory representations. Taken together pTCM and TCM may prove to be part of a general model of declarative memory. (shrink)

The description of named entities in terminological knowledge bases has never been addressed in any depth in terminology. Firm preconceptions, rooted in philosophy, about the only referential function of proper names have presumably led to disparage their inclusion in terminology resources, despite the relevance of named entities having been highlighted by prominent figures in the discipline of terminology. Scholars from different branches of linguistics depart from the conservative stance on proper names and have foregrounded the need for a novel approach, (...) more linguistic than philosophical, to describing proper names. Therefore, this paper proposed a linguistic and terminological approach to the study of named entities when used in scientific discourse, with the purpose of representing them in EcoLexicon, an environmental knowledge base designed according to the premises of Frame-based Terminology. We focused more specifically on named rivers mentioned in a coastal engineering corpus. Inclusion of named entities in terminological knowledge bases requires analyzing the context that surrounds them in specialized texts because these contexts convey specialized knowledge about named entities. For the semantic representation of context, this paper thus analyzed the local syntactic and semantic contexts that surrounded potamonyms in coastal engineering texts and described the semantic annotation of the predicate-argument structure of sentences where a potamonym was mentioned. The semantic variables annotated were the following: semantic category of the arguments; semantic role of the arguments; semantic relation between the arguments; and lexical domain of the verbs. This method yielded valuable insight into the different semantic roles that named rivers played, the entities and processes that participated in the events educed by potamonyms through verbs, and how they all interacted. Furthermore, since arguments are specialized terms and verbs are relational constructs, the analysis of argument structure led to the construction of semantic networks that depicted specialized knowledge about named rivers. These conceptual networks were then used to craft the thematic description of potamonyms. Accordingly, the semantic network and the thematic description not only constituted the representation of a potamonym in EcoLexicon, but also allowed the geographic contextualization of specialized concepts in the terminological resource. (shrink)

Introduction -- Basic concepts -- Previous approaches -- Semantic expressions: introduction -- Formal issues -- Semantic expressions: basic features -- Advanced features -- Applications: capture -- Three little pigs -- Applications: creation.

According to logical theories of meaning, a meaning of an expression can be formalized and encoded in truth conditions. Vagueness of the language and individual differences between people are a challenge to incorporate into the meaning representations. In this paper, we propose a new approach to study truth-conditional representations of vague concepts. For a case study, we selected two natural language quantifiers most and more than half. We conducted two online experiments, each with 90 native English speakers. In (...) the first experiment, we tested between-subjects variability in meaning representations. In the second experiment, we tested the stability of meaning representations over time by testing the same group of participants in two experimental sessions. In both experiments, participants performed the verification task. They verified a sentence with a quantifier (e.g., “Most of the gleerbs are feezda.”) based on the numerical information provided in the second sentence, (e.g., “60% of the gleerbs are feezda”). To investigate between-subject and within-subject differences in meaning representations, we proposed an extended version of the Diffusion Decision Model with two parameters capturing truth conditions and vagueness. We fit the model to responses and reaction times data. In the first experiment, we found substantial between-subject differences in representations of most as reflected by the variability in the truth conditions. Moreover, we found that the verification of most is proportion-dependent as reflected in the reaction time effect and model parameter. In the second experiment, we showed that quantifier representations are stable over time as reflected in stable model parameters across two experimental sessions. These findings challenge semantic theories that assume the truth-conditional equivalence of most and more than half and contribute to the representational theory of vague concepts. The current study presents a promising approach to study semantic representations, which can have a wide application in experimental linguistics. (shrink)

The current article discusses the distinction between affective valence—the degree to which an affective response represents pleasure or displeasure—and semantic valence, the degree to which an object or event is considered positive or negative. To date, measures that reflect positivity and negativity are usually placed under the same conceptual umbrella, with minimal distinction between the modes of valence they reflect. Recent work suggests that what might seem to reflect a monolithic structure of valence has at least two different, confounding (...) underlying sources, affective and semantic, that are fundamentally distinct, dissociable, and that obey different, recognizable rules. The current work discusses this distinction and provides implications for affective science from both the theoretical and the empirical perspective. (shrink)

The overwhelming majority of the attempts in exploring the problems related to quantum logical structures and their interpretation have been based on an underlying set-theoretic syntactic language. We propose a transition in the involved syntactic language to tackle these problems from the set-theoretic to the category-theoretic mode, together with a study of the consequent semantic transition in the logical interpretation of quantum event structures. In the present work, this is realized by representing categorically the global structure of a quantum (...) algebra of events (or propositions) in terms of sheaves of local Boolean frames forming Boolean localization functors. The category of sheaves is a topos providing the possibility of applying the powerful logical classification methodology of topos theory with reference to the quantum world. In particular, we show that the topos-theoretic representation scheme of quantum event algebras by means of Boolean localization functors incorporates an object of truth values, which constitutes the appropriate tool for the definition of quantum truth-value assignments to propositions describing the behavior of quantum systems. Effectively, this scheme induces a revised realist account of truth in the quantum domain of discourse. We also include an Appendix, where we compare our topos-theoretic representation scheme of quantum event algebras with other categorial and topos-theoretic approaches. (shrink)

Computational modeling and eye-tracking were used to investigate how phonological and semantic information interact to influence the time course of spoken word recognition. We extended our recent models to account for new evidence that competition among phonological neighbors influences activation of semantically related concepts during spoken word recognition . The model made a novel prediction: Semantic input modulates the effect of phonological neighbors on target word processing, producing an approximately inverted-U-shaped pattern with a high phonological density advantage at (...) an intermediate level of semantic input—in contrast to the typical disadvantage for high phonological density words in spoken word recognition. This prediction was confirmed with a new analysis of the Apfelbaum et al. data and in a visual world paradigm experiment with preview duration serving as a manipulation of strength of semantic input. These results are consistent with our previous claim that strongly active neighbors produce net inhibitory effects and weakly active neighbors produce net facilitative effects. (shrink)

In this paper, we describe a model that learns semantic representations from the distributional statistics of language. This model, however, goes beyond the common bag‐of‐words paradigm, and infers semantic representations by taking into account the inherent sequential nature of linguistic data. The model we describe, which we refer to as a Hidden Markov Topics model, is a natural extension of the current state of the art in Bayesian bag‐of‐words models, that is, the Topics model of Griffiths, (...) Steyvers, and Tenenbaum (2007), preserving its strengths while extending its scope to incorporate more fine‐grained linguistic information. (shrink)

One way to construct semantic representations in a robust manner is to enhance shallow language processors with semantic components. Here, we provide a model theory for a semantic formalism that is designed for this, namely Robust Minimal Recursion Semantics (RMRS). We show that RMRS supports a notion of entailment that allows it to form the basis for comparing the semantic output of different parses of varying depth.

Abstract Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. (...) We compare the representations of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children’s lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources. (shrink)

In his recent paper, “Justice as Fairness: Political not Metaphysical,” John Rawls makes use of a footnote to disown what to many readers must have seemed one of the most striking and original underlying ideas of his theory of justice, that it “is a part, perhaps the most significant part, of the theory of rational choice.” That Rawls should issue this disclaimer indicates, at least in my view, that he has a much clearer understanding of his theory, and its relationship (...) to rational choice than he did at the time that he wrote A Theory of Justice. As I note in Morals by Agreement, Rawls does not show that principles of justice are principles of rational choice. Hence, in appropriating the idea, I can claim diat I am undertaking a pioneering enterprise. No doubt Thomas Hobbes would have undertaken it had the resources of the theory of rational choice been at his disposal, but I do not intend to pursue counterfactuals in a search for historical antecedents. Moral theory as rational choice theory is, I claim, a new venture. (shrink)

There is an exciting semantic program, defended primarily in the recent works of Donald Davidson and Gilbert Harman, which makes use of both classical truth-conditional semantic method and contemporary transformational syntax, and which is believed to provide illuminating semantical accounts of particular natural languages to which it is applied. I shall call this program, composed of Davidson’s and Harman’s common methodology together with the semantical and metatheoretical claims which it encapsulates, “the D-H Metatheory.”.

The main task of Cognitive Science is to construct concepts and models that would be superordinate to knowledge in the various particular cognitive sciences. In particular, one major objective is to formulate a hypergeneral description of representations that could encompass all descriptions given in subordinate domains.A first basic distinction is between natural and rational representations, i.e. given mental entities and representations that are governed by prescriptive rules coming from logical or scientific thought. In addition, representations must (...) be described in respect to several sources of variability, which are tentatively listed here.Description of natural representations is based on a distinction between taken representations, which are mental events, and type representations, which are lasting structures registered in memory. The connection between them can be modelled through the concept of activation.One advantage of activation models is their large compatibilty, not only with experimental evidence in cognitive psychology, but also with facts and hypotheses in neurosciences, and programming modes or requirements in artificial intelligence. Comprehension of natural language is a highly representative domain in this respect, which exemplifies the power of these concepts. (shrink)

Linguistic Issues in Language Technology (LiLT) is an open-access journal that focuses on the relationships between linguistic insights and language technology. In conjunction with machine learning and statistical techniques, deeper and more sophisticated models of language and speech are needed to make significant progress in both existing and newly emerging areas of computational language analysis. The vast quantity of electronically accessible natural language data (text and speech, annotated and unannotated, formal and informal) provides unprecedented opportunities for data-intensive analysis of linguistic (...) phenomena, which can in turn enrich computational methods. Taking an eclectic view on methodology, LiLT provides a forum for this work. In this volume, contributors offer new perspectives on semantic representations for textual inference. (shrink)

This paper argues for a largely unnoted distinction between relational and modal components in the lexical semantics of verbs. Wehypothesize that many verbs encode two kinds of semantic information:a relationship among participants in a situation and a subset ofcircumstances or time indices at which this relationship isevaluated. The latter we term sublexical modality.We show that linking regularities between semantic arguments andsyntactic functions provide corroborating evidence in favor of thissemantic distinction, noting cases in which the semantic groundingof linking (...) through participant-role properties apparently fails. Thissemantic grounding can be preserved, however, once we abstractaway from sublexical modality in lexical semantic representations.Semantically-based linking constraints are insensitive to the sublexicalmodality component of lexical entries and depend only on informationin a predicator's situational core. (shrink)

The set of English modal verbs is widely recognized to communicate two broad clusters of meanings: epistemic and root modal meanings. A number of researchers have claimed that root meanings are acquired earlier than epistemic ones; this claim has subsequently been employed in the linguistics literature as an argument for the position that English modal verbs are polysemous (Sweetser, 1990). In this paper I offer an alternative explanation for the later emergence of epistemic interpretations by linking them to the development (...) of the child’s theory of mind (Wellman, 1990); if correct, this hypothesis might have important implications for the shape of the semantics of modal verbs. (shrink)

How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, (...) and anyone interested in the development of computational semantics. (shrink)

The authors' model reduces the literature on conceptual representation to a single node: “encyclopedic knowledge.” The structure of conceptual knowledge is not so trivial. By ignoring the phenomena central to reasoning about living things, the authors base their dismissal of semantic systems on inadequate descriptive ground. A better descriptive account is available in the conceptual development literature. Neuropsychologists could import the insights and tasks from cognitive development to improve their studies.

José L. Zalabardo defends a pragmatist account of what grounds the meaning of central semantic discourses--ascriptions of truth, of propositional attitudes, and of meanings. He argues that it is the procedures that regulate acceptance and rejection that give the sentences of these discourses their meanings, and explores the application of the pragmatist template to ethical discourse. The pragmatist approach is presented as an alternative to representationalist accounts of the meaning grounds of declarative sentences, according to which a sentence has (...) the meaning it has as a result of links with the bits of the world that it purports to represent. Zalabardo develops a version of the open-question argument to support the claim that the meaning grounds of the discourses he focuses on cannot receive representationalist accounts. It is generally assumed that a declarative sentence cannot perform the function of representing the world unless it has a representationalist meaning ground. Zalabardo rejects this assumption, arguing that sentences with pragmatist meaning grounds can represent the world in exactly the same sense that sentences with representationalist meaning grounds do. This requires that there are states of affairs that the target sentences represent as obtaining, and Zalabardo develops an account of the nature of the states of affairs that can play this role for sentences with pragmatist meaning grounds. Pragmatist Semantics concludes by developing the suggestion that the meaning grounds of all our representational discourses might be ultimately pragmatist. (shrink)

It is now part and parcel of the official philosophical wisdom that models are essential to the acquisition and organisation of scientific knowledge. It is also generally accepted that most models represent their target systems in one way or another. But what does it mean for a model to represent its target system? I begin by introducing three conundrums that a theory of scientific representation has to come to terms with and then address the question of whether the semantic (...) view of theories, which is the currently most widely accepted account of theories and models, provides us with adequate answers to these questions. After having argued in some detail that it does not, I conclude by pointing out in what direction a tenable account of scientific representation might be sought. (shrink)

Social representations research has tended to focus upon the representations that groups have in relation to some object. The present article elaborates the concept of social representations by pointing to the existence of “alternative representations” as sub-components within social representations. Alternative representations are the ideas and images the group has about how other groups represent the given object. Alternative representations are thus representations of other people's representations. The present article uses data (...) from Moscovici's analysis of the diffusion of psychoanalysis to examine how people engage with alternative representations. It is demonstrated that there can be more or less dialogical relations with alternative representations. The analysis concludes by considering seven “semiotic barriers” which work to neutralise the dialogical potential of alternative representations, thus on the one hand enabling groups to talk about the views of others, while, on the other hand, remaining unchallenged by those views. (shrink)

This paper argues for a representational semantic conception of scientific theories, which respects the bare claim of any semantic view, namely that theories can be characterised as sets of models. RSC must be sharply distinguished from structural versions that assume a further identity of ‘models’ and ‘structures’, which we reject. The practice-turn in the recent philosophical literature suggests instead that modelling must be understood in a deflationary spirit, in terms of the diverse representational practices in the sciences. These (...) insights are applied to some mathematical models, thus showing that the mathematical sciences are not in principle counterexamples to RSC. (shrink)

Contemporary decision theory places crucial emphasis on a family of mathematical results called representation theorems, which relate criteria for evaluating the available options to axioms pertaining to the decision-maker’s preferences. Various claims have been made concerning the reasons for the importance of these results. The goal of this article is to assess their semantic role: representation theorems are purported to provide definitions of the decision-theoretic concepts involved in the evaluation criteria. In particular, this claim shall be examined from the (...) perspective of philosophical theories of the meaning of theoretical terms. (shrink)

In this commentary, I propose that horizontal and vertical dimensions of space are represented together inside a common metrics mechanism located in the parietal cortex. Importantly, this network is also involved in the processing of number magnitudes and environment-directed actions. Altogether, the evidence suggests that different magnitude dimensions could be intertwined with the horizontality and verticality of our world representation.