“Hidden semantics”: what can we learn from the names in an ontology?
“Hidden semantics”: what can we learn from the names in an ontology?
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发表时间：
2012-05
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通讯作者：
Allan Third
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作者：
Allan Third
尽管它们是扁平的、无语义的结构，但本体标识符通常被给予对应于自然语言单词或短语的名称或标签，这些自然语言单词或短语具有关于它们的预期对象的非常密集的信息。我们认为，通过利用这种信息密度，NLG系统应用于本体可以引导选择和构建的句子，以表达有用的本体信息，仅仅通过verbalisations的标识符名称，并通过这样做，他们可以取代非常繁琐和重复的文本所产生的本体verbalisers更短，更简单的文本，更清晰，更容易为人类读者理解。我们指定的本体中的公理是“定义公理”的语言复杂的标识符和分析一个大型语料库的OWL本体，以确定所有定义公理之间的共同模式。通过从本体生成文本，并选择性地包括或省略这些定义公理，我们表明，通过调查，人类读者通常能够推断出隐含编码在标识符短语中的信息，并且不使这种“明显”的信息明确的文本是读者的首选，但传达相同的信息，如较长的文本中，这些信息被明确地拼写出来。
Despite their flat, semantics-free structure, ontology identifiers are often given names or labels corresponding to natural language words or phrases which are very dense with information as to their intended referents. We argue that by taking advantage of this information density, NLG systems applied to ontologies can guide the choice and construction of sentences to express useful ontological information, solely through the verbalisations of identifier names, and that by doing so, they can replace the extremely fussy and repetitive texts produced by ontology verbalisers with shorter and simpler texts which are clearer and easier for human readers to understand. We specify which axioms in an ontology are "defining axioms" for linguistically-complex identifiers and analyse a large corpus of OWL ontologies to identify common patterns among all defining axioms. By generating texts from ontologies, and selectively including or omitting these defining axioms, we show by surveys that human readers are typically capable of inferring information implicitly encoded in identifier phrases, and that texts which do not make such "obvious" information explicit are preferred by readers and yet communicate the same information as the longer texts in which such information is spelled out explicitly.