PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translation

• URL: http://arxiv.org/abs/2103.15075v1
• Date: Sun, 28 Mar 2021 08:01:58 GMT
• Title: PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translation
• Authors: Dimitris Papadopoulos, Nikolaos Papadakis and Nikolaos Matsatsinis
• Abstract summary: We present our submission for the EACL 2021 SRW; a methodology that aims at bridging the gap between high and low-resource languages. We build Neural Machine Translation (NMT) models for English-to-Greek and Greek-to-English based on the Transformer architecture. 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.
• Score: 0.30938904602244344
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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