{"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/discourse-parsing-with-attention-based","title":"Discourse Parsing with Attention-based Hierarchical Neural Networks","arxiv_id":null,"date":"2016-11-01","proceeding":"EMNLP 2016 11","authors":["Qi Li","Tianshi Li","Baobao Chang"],"abstract":"","url_abs":"https://aclanthology.org/D16-1035","url_pdf":"https://aclanthology.org/D16-1035.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":[],"tasks":[{"task_slug":"discourse-parsing","task_name":"Discourse Parsing"},{"task_slug":"document-summarization","task_name":"Document Summarization"},{"task_slug":"feature-engineering","task_name":"Feature Engineering"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/discourse-parsing-on-rst-dt","task":"Discourse Parsing","dataset":"RST-DT","model":"Discourse Parser with Hierarchical Attention","rank_in_archive_order":37,"of":40,"metrics":{"RST-Parseval (Full)":"50.6*","RST-Parseval (Nuclearity)":"66.5*","RST-Parseval (Relation)":"51.4*","RST-Parseval (Span)":"82.2*"},"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}