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Register a new userPersian SemCor: A Bag of Word Sense Annotated Corpus for the Persian Language
الفارسي SEMCOR: كيس من معنى الكلمة المشروحة Corpus اللغة الفارسية
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عادة ما تحقق الأساليب الخاضعة للإشراف أفضل أداء في مشكلة غموض معنى الكلمة.ومع ذلك، فإن عدم توفر إحساس كبير مشروح بالنسبة للعديد من اللغات منخفضة الموارد يجعل هذه الأساليب غير قابل للتطبيق لها في الممارسة العملية.في هذه الورقة، نقوم بتخفيف هذه المشكلة باللغة الفارسية من خلال اقتراح نهج أوتوماتيكي بالكامل للحصول على فارسية الفارسية (Bredemcor)، ككائن مشروح من كيس الفارسية (القوس).قمنا بتقييم الصرص على حد سواء بشكل جوهري ودخله وأظهر أنه يمكن استخدامه بفعالية كمجموعات تدريبية لأنظمة WSD الإشرافية الفارسية.لتشجيع البحث في المستقبل على الغموض في مجال الإحساس بالكلمة الفارسية، فإننا نطلق الولادة في http://nlp.sbu.ac.ir.
Supervised approaches usually achieve the best performance in the Word Sense Disambiguation problem. However, the unavailability of large sense annotated corpora for many low-resource languages make these approaches inapplicable for them in practice. In this paper, we mitigate this issue for the Persian language by proposing a fully automatic approach for obtaining Persian SemCor (PerSemCor), as a Persian Bag-of-Word (BoW) sense-annotated corpus. We evaluated PerSemCor both intrinsically and extrinsically and showed that it can be effectively used as training sets for Persian supervised WSD systems. To encourage future research on Persian Word Sense Disambiguation, we release the PerSemCor in http://nlp.sbu.ac.ir.
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