WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology.

WordNet是一个庞大的词汇数据库，供无数应用程序用于计算语言学。许多提议试图从语义的角度更好地描述它，尤其是解决同义词，分类法和字母学特性，这在特定领域的应用程序中产生了很好的结果。但是，对这种语义描述进行哲学上的转变可以改善这些结果在不同领域中的适用范围。在这个方向上，这项工作通过解决哲学的元属性扩展了WordNet的语义知识。具体来说，我们使用语义类型的概念来提出Wordnet的名词同义词集与基础本体的顶级构造之间的映射规则。为此，我们选择了统一基础本体（UFO），它在结构中显式揭示了概念的哲学元属性，从而形成了完善的Wordnet语义丰富版本。通过对大约5200个样本映射的实验对提出的规则进行了验证，平均准确度为93.5％。此外，为了表明其适用性，该提议被应用于自动学习良好基础的领域本体的任务。