{"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/graphene-a-context-preserving-open","title":"Graphene: A Context-Preserving Open Information Extraction System","arxiv_id":"1808.09463","date":"2018-08-28","proceeding":"COLING 2018 8","authors":["Matthias Cetto","Christina Niklaus","André Freitas","Siegfried Handschuh"],"abstract":"We introduce Graphene, an Open IE system whose goal is to generate accurate,\nmeaningful and complete propositions that may facilitate a variety of\ndownstream semantic applications. For this purpose, we transform syntactically\ncomplex input sentences into clean, compact structures in the form of core\nfacts and accompanying contexts, while identifying the rhetorical relations\nthat hold between them in order to maintain their semantic relationship. In\nthat way, we preserve the context of the relational tuples extracted from a\nsource sentence, generating a novel lightweight semantic representation for\nOpen IE that enhances the expressiveness of the extracted propositions.","url_abs":"http://arxiv.org/abs/1808.09463v1","url_pdf":"http://arxiv.org/pdf/1808.09463v1.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":"graphene-a-context-preserving-open","repo_url":"https://github.com/Lambda-3/Graphene","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"open-information-extraction","task_name":"Open Information Extraction"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}