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Syntactico-Semantic Reasoning using PCFG, MEBN PP Attachment Ambiguity

机译:使用PCFG,MEBN&PP附件模糊性的语法语义推理

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Probabilistic context free grammars (PCFG) have been the core of the probabilistic reasoning based parsers for several years especially in the context of the NLP. Multi entity Bayesian networks (MEBN) a First Order Logic probabilistic reasoning methodology is widely adopted and used method for uncertainty reasoning. Further upper ontology like Probabilistic Ontology Web Language (PR-OWL) built using MEBN takes care of probabilistic ontologies which model and capture the uncertainties inherent in the domain's semantic information. The paper attempts to establish a link between probabilistic reasoning in PCFG and MEBN by proposing a formal description of PCFG driven by MEBN leading to the usage of PR-OWL modeled ontologies in PCFG parsers. Furthermore, the paper outlines an approach to resolve the prepositional phrase (PP) attachment ambiguity using the proposed mapping between PCFG and MEBN.
机译:概率性的背景自由语法(PCFG)是基于概率推理的核心,几年,特别是在NLP的背景下。多实体贝叶斯网络(MEBN)广泛采用了一阶逻辑概率推理方法,采用了不确定性推理的方法。使用MEBN构建的概率本体网络语言(PR-OWL)等进一步的上部本体论负责概率的本体,该概率本体模型和捕获域语义信息中固有的不确定性。本文试图通过提出由MEBN驱动的PCFG的正式描述,在PCFG和MEBN中建立概率推理之间的联系,从而在PCFG解析器中使用PR-OWL建模本体的使用。此外,本文使用PCFG和MEBN之间的建议映射概述了解决介词短语(PP)附件模糊的方法。

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