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Register a new userFrom Constituency to UD-Style Dependency: Building the First Conversion Tool of Turkish
من الدائرة إلى الاعتماد على أسلوب UD: بناء أول أداة تحويل التركية
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تتداول هذه الورقة عن عملية بناء أول أداة تحويل الدائرة إلى التبعية التركية. نقطة الانطلاق لهذا العمل هي دراسة سابقة التي تحولت فيها 10 آلاف من أشجار هيكل العبارة يدويا إلى تركية من Corpus الأصلي Penntreebank. ضمن نطاق هذا المشروع، تم تحويل هذه العبارات التركية هذه الأشجار تلقائيا إلى هياكل التبعية على غرار UD، باستخدام خوارزمية تستند إلى القواعد وخوارزمية لتعلم الآلة محددة لمتطلبات اللغة التركية. تمت مقارنة نتائج الخوارزمية وكلاهما أن نهج التعلم الآلي أثبت أنه أكثر دقة من الخوارزمية القائمة على القواعد. تم تنقيح الناتج من قبل فريق من اللغويين. اتخذت الإصدارات المكررة عباحيات قياسية ذهبية لتقييم الخوارزميات. بالإضافة إلى مساهمتها في مشروع UD مع مجموعة بيانات كبيرة من 10،000 شجرة التبعية التركية، فإن هذا المشروع يفي أيضا فجوة مهمة للأداة التحويل التركية، مما يتيح التعدد السريع من شركة التبعية التي يمكن استخدامها لتدريب محلل التبعية الأفضل وبعد
This paper deliberates on the process of building the first constituency-to-dependency conversion tool of Turkish. The starting point of this work is a previous study in which 10,000 phrase structure trees were manually transformed into Turkish from the original PennTreebank corpus. Within the scope of this project, these Turkish phrase structure trees were automatically converted into UD-style dependency structures, using both a rule-based algorithm and a machine learning algorithm specific to the requirements of the Turkish language. The results of both algorithms were compared and the machine learning approach proved to be more accurate than the rule-based algorithm. The output was revised by a team of linguists. The refined versions were taken as gold standard annotations for the evaluation of the algorithms. In addition to its contribution to the UD Project with a large dataset of 10,000 Turkish dependency trees, this project also fulfills the important gap of a Turkish conversion tool, enabling the quick compilation of dependency corpora which can be used for the training of better dependency parsers.
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