Get out but don't fall down: verb-particle constructions in child language

Authors:
Aline Villavicencio;Marco A. P. Idiart;Carlos Ramisch;Vítor Araújo;Beracah Yankama;Robert Berwick
Affiliations:
Federal University of Rio Grande do Sul, Brazil and MIT;Federal University of Rio Grande do Sul, Brazil;Federal University of Rio Grande do Sul, Brazil;Federal University of Rio Grande do Sul, Brazil;MIT;MIT
Venue:
Proceedings of the Workshop on Computational Models of Language Acquisition and Loss
Year:
2012

Citing 4
Cited 0

The derivation of a large computational lexicon for English from LDOCE

Computational lexicography for natural language processing
Multiword Expressions: A Pain in the Neck for NLP

CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
Evaluating the accuracy of an unlexicalized statistical parser on the PARC DepBank

COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Deep lexical acquisition of verb-particle constructions

Computer Speech and Language

Quantified Score

Hi-index	0.00

Visualization

Abstract

Much has been discussed about the challenges posed by Multiword Expressions (MWEs) given their idiosyncratic, flexible and heterogeneous nature. Nonetheless, children successfully learn to use them and eventually acquire a number of Multiword Expressions comparable to that of simplex words. In this paper we report a wide-coverage investigation of a particular type of MWE: verb-particle constructions (VPCs) in English and their usage in child-produced and child-directed sentences. Given their potentially higher complexity in relation to simplex verbs, we examine whether they appear less prominently in child-produced than in child-directed speech, and whether the VPCs that children produce are more conservative than adults, displaying proportionally reduced lexical repertoire of VPCs or of verbs in these combinations. The results obtained indicate that regardless of any additional complexity VPCs feature widely in children data following closely adult usage. Studies like these can inform the development of computational models for language acquisition.