{"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/generating-knowledge-graph-paths-from-textual","title":"Generating Knowledge Graph Paths from Textual Definitions using Sequence-to-Sequence Models","arxiv_id":"1904.02996","date":"2019-04-05","proceeding":"NAACL 2019 6","authors":["Victor Prokhorov","Mohammad Taher Pilehvar","Nigel Collier"],"abstract":"We present a novel method for mapping unrestricted text to knowledge graph\nentities by framing the task as a sequence-to-sequence problem. Specifically,\ngiven the encoded state of an input text, our decoder directly predicts paths\nin the knowledge graph, starting from the root and ending at the target node\nfollowing hypernym-hyponym relationships. In this way, and in contrast to other\ntext-to-entity mapping systems, our model outputs hierarchically structured\npredictions that are fully interpretable in the context of the underlying\nontology, in an end-to-end manner. We present a proof-of-concept experiment\nwith encouraging results, comparable to those of state-of-the-art systems.","url_abs":"http://arxiv.org/abs/1904.02996v1","url_pdf":"http://arxiv.org/pdf/1904.02996v1.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":"generating-knowledge-graph-paths-from-textual","repo_url":"https://github.com/VictorProkhorov/Text2Path","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}