{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/penelopie-enabling-open-information","title":"PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translation","arxiv_id":"2103.15075","date":"2021-03-28","proceeding":"EACL 2021 2","authors":["Dimitris Papadopoulos","Nikolaos Papadakis","Nikolaos Matsatsinis"],"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.","url_abs":"https://arxiv.org/abs/2103.15075v1","url_pdf":"https://arxiv.org/pdf/2103.15075v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"penelopie-enabling-open-information","repo_url":"https://github.com/lighteternal/PENELOPIE","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"nmt","task_name":"NMT"},{"task_slug":"open-information-extraction","task_name":"Open Information Extraction"},{"task_slug":"translation","task_name":"Translation"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/machine-translation-on-tatoeba-el-to-en","task":"Machine Translation","dataset":"Tatoeba (EL-to-EN)","model":"PENELOPIE (Transformers-based Greek-to-English NMT)","rank_in_archive_order":1,"of":1,"metrics":{"BLEU":"79.3"},"uses_additional_data":true},{"leaderboard":"/sota/machine-translation-on-tatoeba-en-to-el","task":"Machine Translation","dataset":"Tatoeba (EN-to-EL)","model":"PENELOPIE Transformers-based NMT (EN2EL)","rank_in_archive_order":1,"of":1,"metrics":{"BLEU":"76.9"},"uses_additional_data":true},{"leaderboard":"/sota/open-information-extraction-on-carb-oie","task":"Open Information Extraction","dataset":"CaRB OIE benchmark (Greek Use-case)","model":"PENELOPIE Greek OIE","rank_in_archive_order":1,"of":1,"metrics":{"F1":"0.255"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}