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أنماط الاعتمادية للجمل المعقدة والكفوال الدلالي لتحليل التمثيل التجريدي
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تمثيل المعنى التجريدي (AMR) هو تمثيل معنى على مستوى الجملة بناء على هيكل الوسائد المسند.أحد التحديات التي نجدها في تحليل عمرو هي التقاط هيكل الجمل المعقدة التي تعبر عن العلاقة بين المسندات.إن معرفة الجزء الأساسي من هيكل الجملة مقدما قد يكون مفيدا في مثل هذه المهمة.في هذه الورقة، نقدم قائمة أنماط التبعية للإنشاءات الإنكليزية المجامعة المصممة لتحليل عمرو.مع مرحلة مانعة نمط مخصصة، يتم استرداد جميع حدوث إنشاءات الجملة المعقدة من جملة مدخلات.في حين أن بعض المسحاتين لديهم غموض دليون، فإننا نتعامل مع هذه المشكلة من خلال نماذج تصنيف التدريب على البيانات المستمدة من AMR و Wikipedia Corpus، وإنشاء خط أساس جديد للأعمال المستقبلية.سيتم الإعلان عن أنماط الجملة المجامعة المتقدمة وأوصاف عمرو المقابلة.
Abstract Meaning Representation (AMR) is a sentence-level meaning representation based on predicate argument structure. One of the challenges we find in AMR parsing is to capture the structure of complex sentences which expresses the relation between predicates. Knowing the core part of the sentence structure in advance may be beneficial in such a task. In this paper, we present a list of dependency patterns for English complex sentence constructions designed for AMR parsing. With a dedicated pattern matcher, all occurrences of complex sentence constructions are retrieved from an input sentence. While some of the subordinators have semantic ambiguities, we deal with this problem through training classification models on data derived from AMR and Wikipedia corpus, establishing a new baseline for future works. The developed complex sentence patterns and the corresponding AMR descriptions will be made public.
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