Rethinking Grammatical Error Annotation and Evaluation with the Amazon Mechanical Turk

  • Tetreault J
  • Filatova E
  • Chodorow M
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In this paper we present results from two pilot studies which show that using the Amazon Mechanical Turk for preposition error annotation is as effective as using trained raters, but at a fraction of the time and cost. Based on these results, we propose a new evaluation method which makes it feasible to compare two error detection systems tested on different learner data sets.

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  • Joel Tetreault

  • Elena Filatova

  • Martin Chodorow

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