A knowledge extaction system (KEYS) based on UNL knowledge infrastructure

S. Alansary, M. Nagi
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Abstract

With the exponential growth of information available on the internet pages, humans need to extract specific information has also witnessed an ever growing increase. This paper presents KEYS (Knowledge Extraction sYStem). It searches for information inside documents represented in Universal Networking Language (UNL), i.e., in semantic hyper-graphs. This allows for retrieval and extraction practices that are language-independent and semantically-oriented. It is expected to provide high-quality knowledge extraction through a shallow analysis of the source text into the UNL using a specific ontological relations then generate the resulting UNL document into several different target languages in a fully-automatic manner. This is expected to present a novel approach to the topic of identifying named entities; extracting names with all its types from a natural language texts. The Precision measurement of the system is 0.86 while recall measurement is 0.82.
基于UNL知识基础结构的知识抽取系统(KEYS)
随着互联网页面上可用信息的指数级增长,人类提取特定信息的需求也在不断增长。本文提出了KEYS (Knowledge Extraction sYStem)。它搜索用通用网络语言(Universal Networking Language, UNL)表示的文档中的信息,即在语义超图中搜索。这允许独立于语言和面向语义的检索和提取实践。期望通过使用特定的本体论关系对源文本进行浅层分析,从而提供高质量的知识提取,然后以全自动的方式将结果UNL文档生成为几种不同的目标语言。这有望为识别命名实体的主题提供一种新颖的方法;从自然语言文本中提取所有类型的名称。系统的精密度为0.86,召回率为0.82。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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