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Semi-automated typical error annotation for learner English essays: Integrating frameworks

Adrey Kutuzov
National Research University, Higher School of Economics, Russia

Elizaveta Kuzmenko
National Research University, Higher School of Economics, Russia

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Ingår i: Proceedings of the 4th workshop on NLP for Computer Assisted Language Learning at NODALIDA 2015, Vilnius, 11th May, 2015

Linköping Electronic Conference Proceedings 114:5, s. 35-41

NEALT Proceedings Series 26:5, s. 35-41

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Publicerad: 2015-05-06

ISBN: 978-91-7519-036-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

This paper proposes integration of three open source utilities: brat web annotation tool, Freeling suite of linguistic analyzers and Aspell spellchecker. We demonstrate how their combination can be used to pre-annotate texts in a learner corpus of English essays with potential errors and ease human annotators’ work. Spellchecker alerts and morphological analyzer tagging probabilities are used to detect students’ possible errors of most typical sorts. F-measure for the developed pre-annotation framework with regard to human annotation is 0.57, which already makes the system a substantial help to human annotators, but at the same time leaves room for further improvement.

Nyckelord

learner corpora; error annotation; pre-annotation

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