{"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/frame-based-continuous-lexical-semantics","title":"Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles","arxiv_id":"1706.09562","date":"2017-06-29","proceeding":"SEMEVAL 2017 8","authors":["Francis Ferraro","Adam Poliak","Ryan Cotterell","Benjamin Van Durme"],"abstract":"We study how different frame annotations complement one another when learning\ncontinuous lexical semantics. We learn the representations from a tensorized\nskip-gram model that consistently encodes syntactic-semantic content better,\nwith multiple 10% gains over baselines.","url_abs":"http://arxiv.org/abs/1706.09562v1","url_pdf":"http://arxiv.org/pdf/1706.09562v1.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":"frame-based-continuous-lexical-semantics","repo_url":"https://github.com/fmof/tensor-factorization","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}