  In this paper we present our submission for the EACL 2021 SRW; 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.
