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Towards Verbalizing Multilingual N-Ary Relations

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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. 1.

    FBM initiative: http://www.factbasedmodeling.org/.

  2. 2.

    A controlled natural language is a language that a computer can process without any extra information.

  3. 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. 4.

    The tool is available at http://nlp.stanford.edu/downloads/tagger.shtml (last retrieval date: January 9, 2014).

  5. 5.

    Readers may imagine the mapping situations when 〈r1, r2〉 or 〈r2, r3〉 is unique.

References

  • Alexander, C., Ishikawa, S., & Silverstein, M. (1977). A pattern language. New York: Oxford University Press.

    Google Scholar 

  • Baader, F., Calvanese, D., McGuinness, D. L., Nardi, D., & Patel-Schneider, P. F. (2010). The description logic handbook: Theory, implementation and applications. Cambridge: Cambridge University Press.

    Google Scholar 

  • Bakema, G., Zwart Pieter, J., & van der Lek, H. (2002). Volledig communicatiegeoriënteerde informatiemodellering. Netherlands: Academic Service.

    Google Scholar 

  • Bond, F., Fellbaum, C., Hsieh, S.-K., Huang, C.-R., Pease, A., & Vossen, P. (2014). A multilingual lexico-semantic database and ontology. In P. Buitelaar & P. Cimiano (Eds.), The multilingual semantic web. Heidelberg: Springer.

    Google Scholar 

  • Collins, M. (2002). Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithms. Proceedings of the ACL-02 conference on Empirical methods in natural language processing 10 (pp. 1–8). Stroudsburg: Association for Computational Linguistics. doi:10.3115/1118693.1118694.

  • de Cea, G., Gómez-Pérez, A., Montiel-Ponsoda, E., & Suárez-Figueroa, M. (2008). Natural language-based approach for helping in the reuse of ontology design patterns. In A. Gangemi & J. Euzenat (Eds.), EKAW 2008. 5268 (pp. 32–47). Acitrezza: Springer.

    Google Scholar 

  • Demey, J., Jarrar, M., & Meersman, R. (2002). A conceptual markup language that supports interoperability between business rule modeling systems. Proceedings of OTM 2002: COOPIS, DOA, AND ODBASE. 2519, (pp. 19–35). California: Springer.

    Google Scholar 

  • Franconi, E., & Mosca, A. (2013). Towards a core ORM2 language (research note). In Y. Demey & H. Panetto (Eds.), On the Move to Meaningful Internet Systems: OTM 2013 Workshops. 8186 (pp. 448–456). Graz: Springer.

    Google Scholar 

  • Gangemi, A., & Presutti, V. (2009). Ontology design patterns. In S. Staab & R. Studer (Eds.), Handbook of ontologies (2nd ed., pp. 221–243). Heidelberg: Springer.

    Chapter  Google Scholar 

  • Gangemi, A., & Presutti, V. (2010). Towards a pattern science for the semantic web. Semantic Web, 1(1–2), 61–68.

    Google Scholar 

  • Gracia, J., Montiel-Ponsoda, E., Cimiano, P., Gómez-Pérez, A., Buitelaar, P., & McCrae, J. (2012). Challenges for the multilingual web of data. Web Semantics, 11, 63–71.

    Article  Google Scholar 

  • Gromann, D., & Declerck, T. (2014). A cross-lingual correcting and completive method for multilingual ontology labels. In P. Buitelaar & P. Cimiano (Eds.), The multilingual semantic web. Heidelberg: Springer.

    Google Scholar 

  • Haarslev, V., Lutz, C., & Ralf, M. (1999). A description logic with concrete domains and a role-forming predicate operator. Journal of Logic and Computation, 9(3), 351–384. doi:10.1093/logcom/9.3.351.

    Article  MATH  MathSciNet  Google Scholar 

  • Halpin, T., & Curland, M. (2006). Automated verbalization for ORM 2. In R. Meersman, Z. Tari, & P. Herreto (Eds.), On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. 4278 (pp. 1181–1190). Montpellier: Springer.

    Google Scholar 

  • Halpin, T., & Morgan, T. (2008). Information modeling and relational databases (2nd ed.). San Francisco: Morgan Kaufmann.

    Google Scholar 

  • Hearst, M. A. (1992). Automatic acquisition of hyponyms from large text corpora. 14th International Conference on Computational Linguistics (pp. 539–545). Stroudsburg: Association for Computational Linguistics.

    Google Scholar 

  • Heath, C. (2009). The constellation query language. In R. Meersman, P. Herrero, & T. Dillon (Eds.), On the Move to Meaningful Internet Systems: OTM 2009 Workshops. LNCS5872 (pp. 682–691). Vilamoura: Springer.

    Google Scholar 

  • Jardine, D. (1984). Concepts and terminology for the conceptual schema and the information base. Computers and Standards, 3, 3–17.

    Article  Google Scholar 

  • Jarrar, M. (2005). Towards methodological principles for ontology engineering (Ph.D. Thesis). Vrije Universiteit Brussel, Brussel.

    Google Scholar 

  • León-Araúz, P., & Faber, P. (2014). Context and terminology in the multilingual semantic web. In P. Buitelaar & P. Cimiano (Eds.), The multilingual semantic web. Heidelberg: Springer.

    Google Scholar 

  • Marcus, M. P., Marcinkiewicz, M., & Santorini, B. (1993). Building a large annotated corpus of English: The Penn Treebank. Computational Linguistics, 19(2), 313–330.

    Google Scholar 

  • Marshall, I. (1987). Tag selection using probabilistic methods. In R. Garside, G. Sampson, & G. Leech (Eds.), The computational analysis of English: A corpus-based approach (pp. 42–67). London: Longman.

    Google Scholar 

  • Nijssen, S. G., & Halpin, T. A. (1989). Conceptual schema and relational database design: A fact oriented approach (1st ed.). Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Nijssen, M., & Lemmens, I. (2008). Verbalization for business rules and two flavors of verbalization for fact examples. In R. Meersman, Z. Tari, & P. Herrero (Eds.), On the Move to Meaningful Internet Systems: OTM 2008 Workshops. LNCS Vol. 5333 (pp. 760–769). Mexico: Springer.

    Google Scholar 

  • Schreiber, G., Akkermans, H., Anjewierden, A., De Hoog, R., Shadbolt, N. R., Van de Velde, W., et al. (1999). Knowledge engineering and management — the CommonKADS methodology. Cambridge: The MIT Press.

    Google Scholar 

  • Spyns, P., Tang, Y., & Meersman, R. (2008). An ontology engineering methodology for DOGMA. Journal of Applied Ontology, 3(1–2), 13–39 (G. Guizzardi, & T. Halpin, Eds.).

    Google Scholar 

  • Tang, Y., & Meersman, R. (2008). SDRule markup language: Towards modeling and interchanging ontological commitments for semantic decision making. In A. Giurca, D. Gasevic, K. Taveter, A. Giurca, D. Gasevic, & K. Taveter (Eds.), Handbook of research on emerging rule-based languages and technologies: Open solutions and approaches (Vol. Sec. I., pp. 99–123). USA: IGI Publishing. Chapter V.

    Google Scholar 

  • Toutanova, K., Klein, D., Manning, C. D., & Singer, Y. (2003). Feature-rich part-of-speech tagging with a cyclic dependency network. Proceedings of HLT-NAACL 2003. 1 (pp. 252–259). Stroudsburg: Association for Computational Linguistics. doi:10.3115/1073445.1073478.

  • Toutanova, K., & Manning, C. D. (2000). Enriching the knowledge sources used in a maximum entropy part-of-speech tagger. Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000). 13 (pp. 63–70). Stroudsburg: Association for Computational Linguistics. doi:10.3115/1117794.1117802.

  • Xia, F. (2000). The part-of-speech tagging guidelines for the Penn Chinese Treebank (3.0) (Technical report). Philadelphia: University of Pennsylvania.

    Google Scholar 

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Correspondence to Yan Tang Demey .

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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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  • DOI: https://doi.org/10.1007/978-3-662-43585-4_6

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