Corpus Linguistics and Linguistic Theory

Published by De Gruyter Mouton

Volume 9 Issue 2

Issue of Corpus Linguistics and Linguistic Theory

Submit manuscript

Contents
Journal Overview

Publicly Available October 12, 2013

Masthead

Page range: i-iii

Download PDF

May 8, 2013

Complementation of ditransitive verbs in South Asian Englishes: a multifactorial analysis

Marco Schilk, Joybrato Mukherjee, Christopher Nam, Sach Mukherjee

Page range: 187-225

Abstract

This paper examines parallels and differences between South Asian Englishes and British English with regard to various factors driving the selection of verb-complementation patterns. Focusing on the prototypical ditransitive verb give and its complementation, we use large web-derived corpora and distinguish between two possible response cases, one based on the dative and prepositional construction (i.e. the dative alternation), the other including monotransitive complementation. Our data has been additionally coded for a number of potential driving factors, such as pronominality and discourse accessibility of the participants in the constructions. Applying a model-exploration technique we isolate the main driving factors for the varieties under scrutiny (Indian English, Pakistani English and British English) and analyze their influence on pattern selection based on a multinomial logistic regression formulation. Our findings show that, while there is a large area of overlap between the varieties, Pakistani English is closer to British English with regard to relevant driving factors than Indian English. Furthermore, we reveal interesting parallels between all three varieties in the use of monotransitive complementation.

May 8, 2013

Choosing alternatives: Using Bayesian Networks and memory-based learning to study the dative alternation

Daphne Theijssen, Louis ten Bosch, Lou Boves, Bert Cranen, Hans van Halteren

Page range: 227-262

Abstract

In existing research on syntactic alternations such as the dative alternation, ( give her the apple vs. give the apple to her ), the linguistic data is often analysed with the help of logistic regression models. In this article, we evaluate the use of logistic regression for this type of research, and present two different approaches: Bayesian Networks and Memory-based learning. For the Bayesian Network, we use the higher-level semantic features suggested in the literature, while we limit ourselves to lexical items in the memory-based approach. We evaluate the suitability of the three approaches by applying them to a large data set (>11,000 instances) extracted from the British National Corpus, and comparing their quality in terms of classification accuracy, their interpretability in the context of linguistic research, and their actual classification of individual cases. Our main finding is that the classifications are very similar across the three approaches, also when employing lexical items instead of the higher-level features, because most of the alternation is determined by the verb and the length of the two objects (here: her and the apple ).

May 9, 2013

Productive argument selection: Is lexical semantics enough?

Amir Zeldes

Page range: 263-291

Abstract

This paper is concerned with the ability of lexical semantic classes to predict the behavior of argument structures in productively selecting novel lexical material. It will be argued that while lexical semantic classes can explain a great deal about the spectrum of potential arguments and resulting entailments for those arguments, constructions which are synonymous from a formal semantic perspective exhibit significant differences in their empirically observed propensity for argument realization. Using corpus data and methods from Baayen's morphological productivity paradigm, I will show that such differences are not restricted to lexicalized, collocational preferences, but also extend to the readiness with which different constructions admit novel arguments.

May 10, 2013

Book Review

Richard Zhonghua Xiao

Page range: 293-303

About this journal

Objective
Corpus Linguistics and Linguistic Theory (CLLT) is a peer-reviewed journal publishing high-quality original corpus-based research focusing on theoretically relevant issues in all core areas of linguistic research, or other recognized topic areas. It provides a forum for researchers from different theoretical backgrounds and different areas of interest that share a commitment to the systematic and exhaustive analysis of naturally occurring language. Contributions from all theoretical frameworks are welcome but they should be addressed at a general audience and thus be explicit about their assumptions and discovery procedures and provide sufficient theoretical background to be accessible to researchers from different frameworks.

Topics

Corpus Linguistics
Quantitative Linguistics
Phonology
Morphology
Semantics
Syntax
Pragmatics

Article formats
Research Articles

> Information on submission process