Modeling the Complexity and Descriptive Adequacy of Construction Grammars

This paper uses the Minimum Description Length paradigm to model the complexity of CxGs (operationalized as the encoding size of a grammar) alongside their descriptive adequacy (operationalized as the encoding size of a corpus given a grammar). These two quantities are combined to measure the quality of potential CxGs against unannotated corpora, supporting discovery-device CxGs for English, Spanish, French, German, and Italian. The results show (i) that these grammars provide significant generalizations as measured using compression and (ii) that more complex CxGs with access to multiple levels of representation provide greater generalizations than single-representation CxGs

Ontology-driven conceptual modeling: A'systematic literature mapping and review

All rights reserved. Ontology-driven conceptual modeling (ODCM) is still a relatively new research domain in the field of information systems and there is still much discussion on how the research in ODCM should be performed and what the focus of this research should be. Therefore, this article aims to critically survey the existing literature in order to assess the kind of research that has been performed over the years, analyze the nature of the research contributions and establish its current state of the art by positioning, evaluating and interpreting relevant research to date that is related to ODCM. To understand and identify any gaps and research opportunities, our literature study is composed of both a systematic mapping study and a systematic review study. The mapping study aims at structuring and classifying the area that is being investigated in order to give a general overview of the research that has been performed in the field. A review study on the other hand is a more thorough and rigorous inquiry and provides recommendations based on the strength of the found evidence. Our results indicate that there are several research gaps that should be addressed and we further composed several research opportunities that are possible areas for future research

Metamodel Instance Generation: A systematic literature review

Modelling and thus metamodelling have become increasingly important in Software Engineering through the use of Model Driven Engineering. In this paper we present a systematic literature review of instance generation techniques for metamodels, i.e. the process of automatically generating models from a given metamodel. We start by presenting a set of research questions that our review is intended to answer. We then identify the main topics that are related to metamodel instance generation techniques, and use these to initiate our literature search. This search resulted in the identification of 34 key papers in the area, and each of these is reviewed here and discussed in detail. The outcome is that we are able to identify a knowledge gap in this field, and we offer suggestions as to some potential directions for future research.Comment: 25 page

Machine Learning Theory and Practice as a Source of Insight into Universal Grammar

Articl

Introduction

Human languages are inextricably a part of our mind/brain. No other animal has a comparable ability with the same complexity and richness that humans do. An important research goal is to better understand this ability for language: What is it that enables human to acquire and use language the way we do? One way of answering this is to argue that there are aspects of our biology that enable us to acquire and use language. This has been the answer that in modern times has been advocated by generative grammar, in particular in approaches developed based on work by Noam Chomsky (1965, 1986, 2009), although its origins are much older. This approach holds that there are universal aspects of language that all humans share. However, it is at the same time evident that languages also differ: A child growing up in Japan will acquire Japanese whereas a child growing up in Norway will acquire Norwegian. An adequate theory of human language needs to be able to account for both possibly universals and language variation. However, a core question is what such an adequate theory may look like

Systemic-functional linguistics and computation : New directions, new challenges

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Scientific modelling in generative grammar and the dynamic turn in syntax

In this paper, I address the issue of scientific modelling in contemporary linguistics, focusing on the generative tradition. In so doing, I identify two common varieties of linguistic idealisation, which I call determination and isolation respectively. I argue that these distinct types of idealisation can both be described within the remit of Weisberg’s (J Philos 104(12):639–659, 2007) minimalist idealisation strategy in the sciences. Following a line set by Blutner (Theor Linguist, 37(1–2):27–35, 2011) (albeit for different purposes), I propose this minimalist idealisation analysis for a broad construal of the generative linguistic programme and thus cite examples from a wide range of linguistic frameworks including early generative syntax (i.e. Standard Theory, Government and Binding and Principles and Parameters), Minimalism (Chomsky in The minimalist program, MIT Press, Cambridge, 1995), the parallel architecture (Jackendoff in Foundations of language: brain, meaning, grammar, evolution, Oxford University Press, Oxford, 2002) and optimality theory (Prince and Smolensky in Optimality theory: constraint interaction in generative grammar, 1993/2004). Lastly, I claim that from a modelling perspective, the dynamic turn in syntax (Kempson et al. in Dynamic syntax—the flow of language understanding, Blackwell Publishers, Oxford, 2001; Cann et al. in The dynamics of language: an introduction, Elsevier, Oxford, 2005) can be explained as a continuation, as opposed to a marked shift (or revolution), of the generative modelling paradigm (despite radical theory change). Seen in this light, my proposal is an even broader construal of the generative tradition, along scientific modelling lines. Thus, I offer a lens through which to appreciate the scientific contribution of generative grammar, amid an increased resistance to some of its core theoretical posits, in terms of a brand of structural realism in the philosophy of science and specifically scientific modelling.Publisher PDFPeer reviewe