{"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/hhmm-at-semeval-2019-task-2-unsupervised","title":"HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings","arxiv_id":"1905.01739","date":"2019-05-05","proceeding":"SEMEVAL 2019 6","authors":["Saba Anwar","Dmitry Ustalov","Nikolay Arefyev","Simone Paolo Ponzetto","Chris Biemann","Alexander Panchenko"],"abstract":"We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (QasemiZadeh et al., 2019). Our approach separates this task into two independent steps: verb clustering using word and their context embeddings and role labeling by combining these embeddings with syntactical features. A simple combination of these steps shows very competitive results and can be extended to process other datasets and languages.","url_abs":"https://arxiv.org/abs/1905.01739v1","url_pdf":"https://arxiv.org/pdf/1905.01739v1.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":"hhmm-at-semeval-2019-task-2-unsupervised","repo_url":"https://github.com/uhh-lt/semeval2019-hhmm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"task-2","task_name":"Task 2"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1905.01739","atlas_url":"https://app.syntology.ai/?focus=1905.01739","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}