论文标题
在OWL表示中转换UNL图
Transforming UNL graphs in OWL representations
论文作者
论文摘要
从自然语言中提取形式知识（本体）是一个挑战，可以从语义层面上从文本的（半）形式的语言表示中受益。我们建议通过在RDF之上实施通用网络语言（UNL），以实现这种表示。因此，任何语言的陈述的含义都将被大量表示为构成自然语言和形式知识之间的中间立场的RDF-UNL图。特别是，我们表明RDF-UNL图可以使用通用SHACL规则支持内容提取，并且提取事实的推理可以检测到原始文本中的不一致。在UNSEL项目中对这种方法进行了实验，该项目旨在从系统要求/规格中提取本体论表示，以检查它们是否一致，完整和明确。我们的RDF-UNL实施和本文工作示例的所有代码均在https://gitlab.tetras-libre.fr/unl/rdf-unl上公开获得。
Extracting formal knowledge (ontologies) from natural language is a challenge that can benefit from a (semi-) formal linguistic representation of texts, at the semantic level. We propose to achieve such a representation by implementing the Universal Networking Language (UNL) specifications on top of RDF. Thus, the meaning of a statement in any language will be soundly expressed as a RDF-UNL graph that constitutes a middle ground between natural language and formal knowledge. In particular, we show that RDF-UNL graphs can support content extraction using generic SHACL rules and that reasoning on the extracted facts allows detecting incoherence in the original texts. This approach is experimented in the UNseL project that aims at extracting ontological representations from system requirements/specifications in order to check that they are consistent, complete and unambiguous. Our RDF-UNL implementation and all code for the working examples of this paper are publicly available under the CeCILL-B license at https://gitlab.tetras-libre.fr/unl/rdf-unl
