Mohammad Fazleh Elahi


2020

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Recent Developments for the Linguistic Linked Open Data Infrastructure
Thierry Declerck | John Philip McCrae | Matthias Hartung | Jorge Gracia | Christian Chiarcos | Elena Montiel-Ponsoda | Philipp Cimiano | Artem Revenko | Roser Saurí | Deirdre Lee | Stefania Racioppa | Jamal Abdul Nasir | Matthias Orlikowsk | Marta Lanau-Coronas | Christian Fäth | Mariano Rico | Mohammad Fazleh Elahi | Maria Khvalchik | Meritxell Gonzalez | Katharine Cooney
Proceedings of The 12th Language Resources and Evaluation Conference

In this paper we describe the contributions made by the European H2020 project “Prêt-à-LLOD” (‘Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors’) to the further development of the Linguistic Linked Open Data (LLOD) infrastructure. Prêt-à-LLOD aims to develop a new methodology for building data value chains applicable to a wide range of sectors and applications and based around language resources and language technologies that can be integrated by means of semantic technologies. We describe the methods implemented for increasing the number of language data sets in the LLOD. We also present the approach for ensuring interoperability and for porting LLOD data sets and services to other infrastructures, as well as the contribution of the projects to existing standards.

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Terme-à-LLOD: Simplifying the Conversion and Hosting of Terminological Resources as Linked Data
Maria Pia di Buono | Philipp Cimiano | Mohammad Fazleh Elahi | Frank Grimm
Proceedings of the 7th Workshop on Linked Data in Linguistics (LDL-2020)

In recent years, there has been increasing interest in publishing lexicographic and terminological resources as linked data. The benefit of using linked data technologies to publish terminologies is that terminologies can be linked to each other, thus creating a cloud of linked terminologies that cross domains, languages and that support advanced applications that do not work with single terminologies but can exploit multiple terminologies seamlessly. We present Terme-‘a-LLOD (TAL), a new paradigm for transforming and publishing terminologies as linked data which relies on a virtualization approach. The approach rests on a preconfigured virtual image of a server that can be downloaded and installed. We describe our approach to simplifying the transformation and hosting of terminological resources in the remainder of this paper. We provide a proof-of-concept for this paradigm showing how to apply it to the conversion of the well-known IATE terminology as well as to various smaller terminologies. Further, we discuss how the implementation of our paradigm can be integrated into existing NLP service infrastructures that rely on virtualization technology. While we apply this paradigm to the transformation and hosting of terminologies as linked data, the paradigm can be applied to any other resource format as well.