PENELOPIE: enabling open information extraction for the Greek language through machine translationPENELOPIE: enabling open information extraction for the Greek language through machine translation Δημοσίευση σε Συνέδριο Conference Publication 2023-07-102021enThe research work of D.P. was supported by the Hellenic Foundation for Research and Innovation (HFRI) under the HFRI PhD Fellowship grant (Fellowship Number: 50, 2nd call).https://github.com/lighteternal/PENELOPIEIn this work, we present a methodology that aims at bridging the gap between high and low-resource languages in the context of Open Information Extraction, showcasing it on the Greek language. The goals of this paper are twofold: First, we build Neural Machine Translation (NMT) models for English-to-Greek and Greek-to-English based on the Transformer architecture. Second, we leverage these NMT models to produce English translations of Greek text as input for our NLP pipeline, to which we apply a series of pre-processing and triple extraction tasks. Finally, we back-translate the extracted triples to Greek. We conduct an evaluation of both our NMT and OIE methods on benchmark datasets and demonstrate that our approach outperforms the current state-of-the-art for the Greek natural language.http://creativecommons.org/licenses/by/4.0/23–2916th Conference of the European Chapter of the Association for Computational Linguistics: Student Research WorkshopProceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research WorkshopPapadopoulos_et_al_EACL_2021.pdfChania [Greece]Library of TUC2023-07-10application/pdf708.5 kBfree Papadopoulos Dimitrios Παπαδοπουλος Δημητριος Papadakis Nikolaos Matsatsinis Nikolaos Ματσατσινης Νικολαος Association for Computational Linguistics Nlp Machine-translation Information-extraction Greek-language Oie-systems