Abstract
The idea of a Multilingual Semantic Web is to provide access to knowledge available on the Semantic Web (SW) to speakers of different languages. In this chapter, we concentrate on a particular aspect of the Multilingual Semantic Web vision and discuss the challenge of multilingual verbalization for conceptual models. Natural verbalizations require n-ary fact types, whereas popular Description Logic (DL) dialects [such as those used by the Web Ontology Language (OWL)] only support binary fact types. We use a Fact-Based Modelling (FBM) approach because it supports n-ary verbalization. We also discuss the use of natural language taggers in the creation of these models, which preserves the natural form of those verbalization patterns. Patterns that are typical and representative are studied in English and Chinese. In order to publish such models to the SW, we use objectification (i.e. model reification) to transform n-ary fact types to a binary form.
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Notes
- 1.
FBM initiative: http://www.factbasedmodeling.org/.
- 2.
A controlled natural language is a language that a computer can process without any extra information.
- 3.
The ORM family contains ORM (the initial ORM) and ORM2 (the second generation of ORM). Including the update of graphical notations, ORM2 also contains a few extensions to the initial ORM, such as constraint modality and derivation rules. In this chapter, we use the term “ORM” for the whole ORM family.
- 4.
The tool is available at http://nlp.stanford.edu/downloads/tagger.shtml (last retrieval date: January 9, 2014).
- 5.
Readers may imagine the mapping situations when 〈r1, r2〉 or 〈r2, r3〉 is unique.
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Demey, Y.T., Heath, C. (2014). Towards Verbalizing Multilingual N-Ary Relations. In: Buitelaar, P., Cimiano, P. (eds) Towards the Multilingual Semantic Web. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43585-4_6
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