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Register a new userA (Mostly) Symbolic System for Monotonic Inference with Unscoped Episodic Logical Forms
نظام رمزي (في الغالب) للاستدلال الرخيصي مع أشكال منطقية غير مستقرة
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نقوم بتطبيق إضفاء الطابع الرسمي على الاستدلال الطبيعي الذي يشبه المنطق الطبيعي باستخدام أشكال منطقية غير مستقرة غير مستقرة (ULFS) بواسطة كيم وآخرون.(2020).نوضح قدرة هذا النظام على التعامل مع مجموعة متنوعة من الظواهر الدلالية الصعبة باستخدام DataSet Fracas (Cooper et al.، 1996).تعطي هذه النتائج أدلة تجريبية للمطالبات السابقة أن ULF هو تمثيل مناسب للتوسط في استنتاجات من المنطق الطبيعي.
We implement the formalization of natural logic-like monotonic inference using Unscoped Episodic Logical Forms (ULFs) by Kim et al. (2020). We demonstrate this system's capacity to handle a variety of challenging semantic phenomena using the FraCaS dataset (Cooper et al., 1996). These results give empirical evidence for prior claims that ULF is an appropriate representation to mediate natural logic-like inferences.
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Episodic Logic: Unscoped Logical Form'' (EL-ULF) is a semantic representation capturing predicate-argument structure as well as more challenging aspects of language within the Episodic Logic formalism. We present the first learned approach for parsin
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Deep learning (DL) based language models achieve high performance on various benchmarks for Natural Language Inference (NLI). And at this time, symbolic approaches to NLI are receiving less attention. Both approaches (symbolic and DL) have their adva
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