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Online Reasoning for Ontology-Based Error Detection in Text

机译:在文本中基于本体的错误检测在线推理

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Detecting error in text is a difficult task. Current methods use a domain ontology to identify elements in the text that contradicts domain knowledge. Yet, these methods require manually defining the type of errors that are expected to be found in the text before applying them. In this paper we propose a new approach that uses logic reasoning to detect errors in a statement from text online. Such approach applies Information Extraction to transform text into a set of logic clauses. The logic clauses are incorporated into the domain ontology to determine if it contradicts the ontology or not. If the statement contradicts the domain ontology, then the statement is incorrect with respect to the domain knowledge. We have evaluated our proposed method by applying it to a set of written summaries from the domain of Ecosystems. We have found that this approach, although depending on the quality of the Information Extraction output, can identify a significant amount of errors. We have also found that modeling elements of the ontology (i.e., property domain and range) likewise affect the capability of detecting errors.
机译:检测文本中的错误是一项艰巨的任务。当前方法使用域本体来识别文本中的元素,违反域知识。然而,这些方法需要手动定义在应用之前在文本中找到的错误类型。在本文中,我们提出了一种新的方法,它使用逻辑推理来检测在线文本中的声明中的错误。此类方法适用信息提取将文本转换为一组逻辑条款。逻辑条款被纳入域本体,以确定它是否与本体或不相矛盾。如果声明与域本体进行矛盾,则对域知识的语句不正确。我们通过将其应用于生态系统领域的一套书面摘要来评估我们提出的方法。我们发现这种方法,虽然根据信息提取输出的质量,但可以识别大量的错误。我们还发现本体的建模元素(即属性域和范围)同样影响检测错误的能力。

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