Correction Annotation for Non-Native Arabic Texts: Guidelines and Corpus

We present our correction annotation guidelines to create a manually corrected nonnative (L2) Arabic corpus. We develop our approach by extending an L1 large-scale Arabic corpus and its manual corrections, to include manually corrected non-native Arabic learner essays. Our overarching goal is to use the annotated corpus to develop components for automatic detection and correction of language errors that can be used to help Standard Arabic learners (native and non-native) improve the quality of the Arabic text they produce. The created corpus of L2 text manual corrections is the largest to date. We evaluate our guidelines using inter-annotator agreement and show a high degree of consistency.

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