Abstract
To enable knowledge access across languages, ontologies, mostly represented only in English, need to be translated into different languages. The main challenge in translating ontologies with machine translation is to disambiguate an ontology label with respect to the domain modelled by the ontology itself; however, a crucial requirement is to have translations validated by experts before the ontologies are deployed. Real-world applications have to implement a support system addressing this task to help experts in validating automatically generated translations. In this paper, we present ESSOT, an Expert Supporting System for Ontology Translation. The peculiarity of this system is to exploit the semantic information of the label’s context to improve the quality of label translations. The system has been tested within the Organic.Lingua project by translating the modelled ontology in three languages, whereby the results are compared with translations provided by the Microsoft Translator API. The provided results demonstrate the viability of our proposed approach.
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Notes
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Translation performed on 2.3.2016.
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For more information how to invoke the service, see also: http://server1.nlp.insight-centre.org/otto/rest_service.html.
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Wikimedia Foundation/Mediawiki: http://www.mediawiki.org.
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Though MoKi allows to model both ontological and procedural knowledge, here we will limit our description only to the features for building multilingual ontologies.
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A read-only version, but with all functionalities available, of the MoKi instance described in this paper is available at https://dkmtools.fbk.eu/moki/3_5/essot/.
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Acknowledgement
This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 and the European Unions Horizon 2020 programme MixedEmotions (Grant Number 644632).
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Arcan, M., Dragoni, M., Buitelaar, P. (2016). ESSOT: An Expert Supporting System for Ontology Translation. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_6
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