基于PCFG、MEBN和PP附件歧义的句法语义推理

Shrinivasan Patnaikuni, S. Gengaje
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引用次数: 3

摘要

近年来,概率上下文无关语法(PCFG)一直是基于概率推理的解析器的核心,特别是在自然语言处理领域。多实体贝叶斯网络(MEBN)是一阶逻辑概率推理方法,是一种被广泛采用和应用的不确定性推理方法。进一步的上层本体,如使用MEBN构建的概率本体Web语言(PR-OWL),则负责建模和捕获领域语义信息中固有的不确定性的概率本体。本文通过提出由MEBN驱动的PCFG的形式化描述,从而在PCFG解析器中使用PR-OWL建模的本体,试图在PCFG和MEBN中建立概率推理之间的联系。此外,本文还提出了一种利用PCFG和MEBN之间的映射来解决介词短语(PP)连接歧义的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Syntactico-Semantic Reasoning using PCFG, MEBN & PP Attachment Ambiguity
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.
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