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Register a new userConversational Negation using Worldly Context in Compositional Distributional Semantics
نفي المحادثة باستخدام السياق الدنيوي في دلالات التوزيع التركيبية
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نقترح إطارا لنموذج نفي محادثة تشغيلية من خلال تطبيق السياق الدنيوي (المعرفة السابقة) على النفي المنطقي في دلالات التوزيع التركيبية.بالنظر إلى كلمة، يمكن لإطارنا أن يخلق نفيها مما يشبه كيفية إدراك البشر النفي.يقوم الإطار بتصحيح النفي المنطقي معاني الوزن أقرب إلى التسلسل الهرمي الاستيباري أكثر من المعاني إلى حد بعيد.الإطار المقترح مرن لاستيعاب خيارات مختلفة من النفي المنطقي والتركيبات وتوليد السياق الدنيوي.على وجه الخصوص، نقترح ونحفز النفي المنطقي الجديد باستخدام مصفوفة معكوس.نحن نقوم بالتحقق من حساسية إطار نفي المحادثة لدينا عن طريق إجراء تجارب، واستفادة من مصفوف الكثافة لتشفير معلومات التسلل المتدرجة.نستنتج أن مزيج النفي للطرح والمسار في الأساس من الكلمة المنفذة تعطي أعلى ارتباط بيرسون ب 0.635 مع التقييمات البشرية.
We propose a framework to model an operational conversational negation by applying worldly context (prior knowledge) to logical negation in compositional distributional semantics. Given a word, our framework can create its negation that is similar to how humans perceive negation. The framework corrects logical negation to weight meanings closer in the entailment hierarchy more than meanings further apart. The proposed framework is flexible to accommodate different choices of logical negations, compositions, and worldly context generation. In particular, we propose and motivate a new logical negation using matrix inverse. We validate the sensibility of our conversational negation framework by performing experiments, leveraging density matrices to encode graded entailment information. We conclude that the combination of subtraction negation and phaser in the basis of the negated word yields the highest Pearson correlation of 0.635 with human ratings.
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