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Register a new userMonotonicity Marking from Universal Dependency Trees
ترميز راتمة من أشجار الاعتمادية العالمية
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تحليل التبعية هي أداة تستخدم على نطاق واسع في مجال معالجة اللغة الطبيعية واللغويات الحاسوبية.ومع ذلك، فهناك أي عمل لا يربط بتحليل التبعية إلى رتابة، وهو جزء أساسي من المنطق واللغوي.في هذه الورقة، نقدم نظام يعلق تلقائيا على معلومات رتابة تستند إلى أشجار تحليل التبعية الشاملة.يستخدم نظامنا حقائق عاطفية على مستوى سطح الأرض حول الكميات والبنود المعجمية ومعلومات القطبية على مستوى الرمز المميز.قمنا بمقارنة أداء نظامنا مع الأنظمة الحالية في الأدبيات، بما في ذلك NATLOG و CCG2MONO، على مجموعة بيانات تقييم صغيرة.تظهر النتائج أن نظامنا يتفوق على Natlog و CCG2MONO.
Dependency parsing is a tool widely used in the field of Natural language processing and computational linguistics. However, there is hardly any work that connects dependency parsing to monotonicity, which is an essential part of logic and linguistic semantics. In this paper, we present a system that automatically annotates monotonicity information based on Universal Dependency parse trees. Our system utilizes surface-level monotonicity facts about quantifiers, lexical items, and token-level polarity information. We compared our system's performance with existing systems in the literature, including NatLog and ccg2mono, on a small evaluation dataset. Results show that our system outperforms NatLog and ccg2mono.
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