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HOO 2012 : a report on the preposition and determiner error correction shared task
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Using edit distance to analyse errors in a natural language to logic translation corpus
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Abstract:
We have assembled a large corpus of student submissions to an automatic grading system, where the subject matter involves the translation of natural language sentences into propositional logic. Of the 2.3 million translation instances in the corpus, 286,000 (approximately 12%) are categorized as being in error. We want to understand the nature of the errors that students make, so that we can develop tools and supporting infrastructure that help students with the problems that these errors represent. With this aim in mind, this paper describes an analysis of a significant proportion of the data, using edit distance between incorrect answers and their corresponding correct solutions, and the associated edit sequences, as a means of organising the data and detecting categories of errors. We demonstrate that a large proportion of errors can be accounted for by means of a small number of relatively simple error types, and that the method draws attention to interesting phenomena in the data set. ; 8 page(s)
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Keyword:
080100 Artificial Intelligence and Image Processing
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URL: http://hdl.handle.net/1959.14/177827
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Proceedings of the EACL 2012 Workshop on Computational Linguistics and Writing: Linguistic and cognitive aspects of document creation and document engineering (CL&W 2012)
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In: Proceedings of the EACL 2012 Workshop on Computational Linguistics and Writing: Linguistic and cognitive aspects of document creation and document engineering (CL&W 2012). Edited by: Piotrowski, Michael; Mahlow, Cerstin; Dale, Robert (2012). Stroudsburg, PA, USA: ACL. (2012)
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Using edit distance to analyse errors in a natural language to logic translation corpus
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Collocations in multilingual natural language generation : Lexical functions meet Lexical functional grammar
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Generating subsequent reference in shared visual scenes : computation vs. re-use
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Building an audio-visual corpus of Australian English : large corpus collection with an economical portable and replicable Black Box
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GRE3D7 : A Corpus of distinguishing descriptions for objects in visual scenes
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The Impact of visual context on the content of referring expressions
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Building an audio-visual corpus of Australian English : large corpus collection with an economical portable and replicable Black Box
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