ندرس مهمة التعلم وتقييم embeddings الصينية.نقوم أولا بإنشاء مجموعة بيانات تقييم جديدة تحتوي على مرادفات IDIOM والمتضادات.قد لا تكون مراقبة أن طرق تضمين الكلمة الصينية الحالية قد لا تكون مناسبة لتعلم Adiom AregBeddings، ونحن نقدم طريقة قائمة على بيرت التي تتعلم مباشرة أن تضمين ناقلات التعابير الفردية.نحن نقارن تجريبيا الأساليب الحالية وطريقتنا.نجد أن طريقتنا تتفوق بشكل كبير على الأساليب الحالية على مجموعة بيانات التقييم التي شيدناها.
We study the task of learning and evaluating Chinese idiom embeddings. We first construct a new evaluation dataset that contains idiom synonyms and antonyms. Observing that existing Chinese word embedding methods may not be suitable for learning idiom embeddings, we further present a BERT-based method that directly learns embedding vectors for individual idioms. We empirically compare representative existing methods and our method. We find that our method substantially outperforms existing methods on the evaluation dataset we have constructed.
References used
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