Semantic cognition: a re-examination of the recurrent network "hub" model

This paper explores a model of “semantic cognition” first described in Rogers et al. (2004). This model was shown to reproduce the behaviour of neurological patients who perform poorly on a variety of tests of semantic knowledge; thus purporting to provide a comprehensive explanation for semantic deficits as found in patients with semantic dementia and, as extended in Lambon Ralph, Lowe, and Rogers (2007), individuals with herpes simplex virus encephalitis. Therefore, not only does the model emulate these semantic impairments, it also underpins a theoretical account of such memory disturbances. We report preliminary results arising from an attempted reimplementation of the Rogers et al. model. Specifically, while we were able to successfully reimplement the fully-functioning model and recreate “normal” behaviour, our attempts to replicate the behaviour of semantically impaired patients by lesioning the model were mixed. Our results suggest that while semantic impairments reminiscent of patients may arise when the Rogers et al. model is lesioned, such impairments are not a necessary consequence of the model. We discuss the implications of these apparently negative results for the Rogers et al. account of semantic cognition

The syntactic derivations of interrogative verbs in Amis and Kavalan

Interrogative words that denote ‘what’, ‘how’, ‘where’, and ‘how many’ in Amis and Kavalan have the same morphosyntactic distribution as verbs. The present paper argues that their use as verbs is not due to unconstrained lexical idiosyncrasies, but exhibits consistent syntactic and semantic patterns. Their grammatical properties and restrictions follow from the interaction of the following factors: the inherent semantics of interrogative words, the available interpretation of the question where they occur, the verbal structures of the voice markers, and the syntactic principles and constraints like the Head Movement Constraint or the Transparence Condition. The syntactic analysis advocated in this paper can extend to other atypical non-interrogative verbs in the two languages and makes falsifiable predictions about what interrogative words can and cannot be used as verbs

Linguistic DNA: Investigating Conceptual Change in Early Modern English Discourse

This article describes the background and premises of the AHRC-funded project, ‘The Linguistic DNA of Modern Western Thought’. We offer an empirical, encyclopaedic approach to historical semantics regarding ‘conceptual history’, i.e. the history of concepts that shape thought, culture and society in a particular period. We relate the project to traditional work in conceptual and semantic history and define our object of study as the discursive concept, a category of meaning encoded linguistically as a cluster of expressions that co-occur in discourse. We describe our principal data source, EEBO-TCP, and introduce our key research interests, namely, the contexts of conceptual change, the semantic structure of lexical fields and the nature of lexicalisation pressure. We outline our computational processes, which build upon the theoretical definition of discursive concepts, to discover the linguistically encoded forms underpinning the discursive concepts we seek to identify in EEBO-TCP. Finally, we share preliminary results via a worked example, exploring the discursive contexts in which paradigmatic terms of key cultural concepts emerge. We consider the extent to which particular genres, discourses and users in the early modern period make paradigms, and examine the extent to which these contexts determine the characteristics of key concepts

Ontology Building Using Parallel Enumerative Structures

National audienceThe semantics of a text is carried by both the natural language it contains and its layout. As ontology building processes have so far taken only plain text into consideration, our aim is to elicit its textual structure. We focus here on parallel enumerative structures because they bear implicit or explicit hierarchical relations, they have salient visual properties, and they are frequently found in corpora. We have defined a process which identifies them in a text, translates them into ontology structures and finally links such structures to the concepts of an existing ontology. We have assessed this process on Wikipedia encyclopaedic articles as they are rich in definitions and statements, and contain many enumerations. The many ontology structures we have obtained are thus used to enrich an ontology which we had automatically built from database specification documents

Key steps for the construction of a glossary based on FunGramKB Term Extractor and referred to international cooperation against organised crime and terrorism

The employment of new technological instruments for the processing of natural languages is crucial to improve the way humans interact with machines. The Functional Grammar Knowledge Base (FunGramKB henceforth) has been designed to cover Natural Language Processing (NLP henceforth) tasks in the area of Artificial Intelligence. The multipurpose lexical conceptual knowledge base FunGramKB is capable of combining linguistic knowledge and human cognitive abilities within its system as a whole. The conceptual module of FunGramKB contains both common-sense knowledge (Ontology), procedural knowledge (Cognicon) as well as knowledge about named entities representing people, places, organisations or other entities (Onomasticon). The Onomastical component is used to process the information from the perspective of specialised discourse. The definition in Natural Language of a consistent list of encyclopaedic terms existent referred to the legislation and to entities which fight against organised crime and terrorism existent in the GCTC would be the stepping stone for the future development of the Onomasticon. The FunGramKB Term Extractor (FGKBTE henceforth) is used to process the information. To cope with the inclusion of the terms in the Onomasticon according to the Conceptual Representation Language (COREL henceforth) schemata, the DBpedia project has been of paramount importance to develop specific patterns for the structure of the definitions.El empleo de nuevas herramientas tecnológicas para el Procesamiento del Lenguaje Natural (PLN en adelante) es fundamental para mejorar la forma en que las máquinas se relacionan con los seres humanos. FunGramKB ha sido diseñada para abordar tareas de PLN inmersas en el área de la Inteligencia Artificial. La base de conocimiento léxico conceptual multipropósito FunGramKB es capaz de combinar el conocimiento lingüístico con las habilidades cognitivas humanas dentro de su sistema como conjunto. El modulo conceptual de FunGramKB se basa en el sentido común (Ontología) y en el conocimiento procedimental (Cognicón), a la vez que en el conocimiento sobre entidades nombradas que representan personas, lugares, organizaciones u otras entidades (Onomasticon). La definición en Lenguaje Natural de una lista consistente de términos enciclopédicos concerniente tanto a instrumentos legales como a organizaciones que luchan contra el crimen organizado y el terrorismo que se ha incluido en el GCTC supondrá un gran adelanto en aras al futuro desarrollo del Onomasticon. El FGKBTE se usa para procesar la información. Con vistas a incluir los términos en el Onomasticón de acuerdo al esquema COREL, el proyecto DBpedia ha sido de una importancia fundamental para desarrollar patrones determinados con los que estructurar las definiciones.Universidad de Granada. Departamento de Filologías Inglesa y Alemana. Máster en Lingüística y Literatura Inglesas, curso 2013-201

Using natural language patterns for the development of ontologies

The combination of certain linguistic units that recurrently appear in text genres has attracted the attention of many researchers in several domains, as they can provide valuable information about different types of relations. In this paper, the focus will be on some of these combinatory units, referred to as Lexico-Syntactic Patterns (LSPs) that provide information about conceptual relations. The aim of this research is to detect recurrent patterns that express some of the most common conceptual relations present in ontologies. The purpose of this paper is to present the different strategies we have followed to identify LSPs which correspond to some of the main ontological relations, as well as an excerpt of the repository of LSPs that is currently being built

A corpus-based approach to building a conceptual-based terminological resource

UIDB/03213/2020 UIDP/03213/2020This paper aims to describe a text-mining approach on a domain corpus (cork) within the theoretical framework of the dual dimension of terminology to create a terminological dictionary and correlate it with an ontology. We will make some considerations on (i) domain specificities; (ii) lexical markers; (iii) automatic corpus processing using Sketch Engine; (iv) representation of lexical networks using CmapTools; and (v) representation of the concept system using Protégé. The goal of the ontology is to logically support the coherence and quality of the natural language definitions contained in the terminological resource.publishersversionpublishe