Το work with title PENELOPIE: enabling open information extraction for the Greek language through machine translation by Papadopoulos Dimitrios, Papadakis Nikolaos, Matsatsinis Nikolaos is licensed under Creative Commons Attribution 4.0 International
Bibliographic Citation
D. Papadopoulos, N. Papadakis, and N. Matsatsinis, “PENELOPIE: enabling open information extraction for the Greek language through machine translation,” in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (EACL 2021), virtual event, 2021, pp. 23–29, doi: 10.18653/v1/2021.eacl-srw.4.
https://doi.org/10.18653/v1/2021.eacl-srw.4
In 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.