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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