Towards an n-grammar of English
Type de document :
Partie d'ouvrage
Titre :
Towards an n-grammar of English
Auteur(s) :
Cappelle, Bert [Auteur]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Grabar, Natalia [Auteur]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Grabar, Natalia [Auteur]
Savoirs, Textes, Langage (STL) - UMR 8163 [STL]
Titre de l’ouvrage :
Constructionist Approaches to Second Language Acquisition and Foreign Language Teaching
Date de publication :
2016-10
Mot(s)-clé(s) en anglais :
ESL/EFL
POS n-grams
frequency
constructicon
grammar teaching
POS n-grams
frequency
constructicon
grammar teaching
Discipline(s) HAL :
Sciences de l'Homme et Société/Linguistique
Résumé en anglais : [en]
In this chapter, it is shown how we can develop a new type of learner’s or student’s grammar based on n-grams (sequences of 2 or 3, 4, etc. items) automatically extracted from a large corpus, such as the Corpus of Contemporary ...
Lire la suite >In this chapter, it is shown how we can develop a new type of learner’s or student’s grammar based on n-grams (sequences of 2 or 3, 4, etc. items) automatically extracted from a large corpus, such as the Corpus of Contemporary American English (COCA). The notion of n-gram and its primary role in statistical language modelling is first discussed. The part-of-speech (POS) tagging provided for lexical n-grams in COCA is then demonstrated to be useful for the identification of frequent structural strings in the corpus. We propose using the hundred most frequent POS-based 5-grams as the content around which an ‘n-grammar’ of English can be constructed. We counter some obvious objections to this approach (e.g. that these patterns only scratch the surface, or that they display much overlap among them) and describe extra features for this grammar, relating to the patterns’ productivity, corpus dispersion, functional description and practice potential.Lire moins >
Lire la suite >In this chapter, it is shown how we can develop a new type of learner’s or student’s grammar based on n-grams (sequences of 2 or 3, 4, etc. items) automatically extracted from a large corpus, such as the Corpus of Contemporary American English (COCA). The notion of n-gram and its primary role in statistical language modelling is first discussed. The part-of-speech (POS) tagging provided for lexical n-grams in COCA is then demonstrated to be useful for the identification of frequent structural strings in the corpus. We propose using the hundred most frequent POS-based 5-grams as the content around which an ‘n-grammar’ of English can be constructed. We counter some obvious objections to this approach (e.g. that these patterns only scratch the surface, or that they display much overlap among them) and describe extra features for this grammar, relating to the patterns’ productivity, corpus dispersion, functional description and practice potential.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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