A Pipeline Approach to Supervised Error Correction for the QALB-2014 Shared Task
نویسندگان
چکیده
This paper describes our submission to the ANLP-2014 shared task on automatic Arabic error correction. We present a pipeline approach integrating an error detection model, a combination of characterand word-level translation models, a reranking model and a punctuation insertion model. We achieve an F1 score of 62.8% on the development set of the QALB corpus, and 58.6% on the official test set.
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