في هذه الورقة، نقدم الإصدار اليوناني من خاطئ أداة التوضيح التلقائية (براينت وآخرون، 2017)، والتي أطلقنا عليها اسم Elerrant.وظائف خاطئة كتصنيف نوع من نوع الخطأ القاعدة واستخدامه كأداة التقييم الرئيسية للأنظمة المشاركة في BEA-2019 (براينت وآخرون، 2019) مهمة مشتركة.هنا، نناقش الاختلافات النحوية والمورفولوجية بين الإنجليزية واليونانية وكيف أثرت هذه الاختلافات على تطوير السائل.نحن نقدم أيضا أول كوربوس اليونانية الأصلية (GNC) و Wikiedits Corpus اليونانية (GWE)، ومجموعات بيانات تقييم جديدة مع أخطاء من المتعلمين اليونانيين الأصليين وتحرير صفحات الحديث في ويكيبيديا على التوالي.تستخدم هذان البيانات اثنين لتقييم السائل.هذه الورقة هي جزء وحيد من صورة أكبر توضح محاولة حل مشكلة لغات الموارد المنخفضة في NLP، في حالتنا اليونانية.
In this paper, we introduce the Greek version of the automatic annotation tool ERRANT (Bryant et al., 2017), which we named ELERRANT. ERRANT functions as a rule-based error type classifier and was used as the main evaluation tool of the systems participating in the BEA-2019 (Bryant et al., 2019) shared task. Here, we discuss grammatical and morphological differences between English and Greek and how these differences affected the development of ELERRANT. We also introduce the first Greek Native Corpus (GNC) and the Greek WikiEdits Corpus (GWE), two new evaluation datasets with errors from native Greek learners and Wikipedia Talk Pages edits respectively. These two datasets are used for the evaluation of ELERRANT. This paper is a sole fragment of a bigger picture which illustrates the attempt to solve the problem of low-resource languages in NLP, in our case Greek.
References used
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