{"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/building-context-aware-clause-representations","title":"Building Context-aware Clause Representations for Situation Entity Type Classification","arxiv_id":"1809.07483","date":"2018-09-20","proceeding":"EMNLP 2018 10","authors":["Zeyu Dai","Ruihong Huang"],"abstract":"Capabilities to categorize a clause based on the type of situation entity\n(e.g., events, states and generic statements) the clause introduces to the\ndiscourse can benefit many NLP applications. Observing that the situation\nentity type of a clause depends on discourse functions the clause plays in a\nparagraph and the interpretation of discourse functions depends heavily on\nparagraph-wide contexts, we propose to build context-aware clause\nrepresentations for predicting situation entity types of clauses. Specifically,\nwe propose a hierarchical recurrent neural network model to read a whole\nparagraph at a time and jointly learn representations for all the clauses in\nthe paragraph by extensively modeling context influences and inter-dependencies\nof clauses. Experimental results show that our model achieves the\nstate-of-the-art performance for clause-level situation entity classification\non the genre-rich MASC+Wiki corpus, which approaches human-level performance.","url_abs":"http://arxiv.org/abs/1809.07483v1","url_pdf":"http://arxiv.org/pdf/1809.07483v1.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":"building-context-aware-clause-representations","repo_url":"https://github.com/baokuiwang/context_aware_situation_entity","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"type","task_name":"Vocal Bursts Type Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}