{"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/nugget-proposal-networks-for-chinese-event","title":"Nugget Proposal Networks for Chinese Event Detection","arxiv_id":"1805.00249","date":"2018-05-01","proceeding":"ACL 2018 7","authors":["Hongyu Lin","Yaojie Lu","Xianpei Han","Le Sun"],"abstract":"Neural network based models commonly regard event detection as a word-wise\nclassification task, which suffer from the mismatch problem between words and\nevent triggers, especially in languages without natural word delimiters such as\nChinese. In this paper, we propose Nugget Proposal Networks (NPNs), which can\nsolve the word-trigger mismatch problem by directly proposing entire trigger\nnuggets centered at each character regardless of word boundaries. Specifically,\nNPNs perform event detection in a character-wise paradigm, where a hybrid\nrepresentation for each character is first learned to capture both structural\nand semantic information from both characters and words. Then based on learned\nrepresentations, trigger nuggets are proposed and categorized by exploiting\ncharacter compositional structures of Chinese event triggers. Experiments on\nboth ACE2005 and TAC KBP 2017 datasets show that NPNs significantly outperform\nthe state-of-the-art methods.","url_abs":"http://arxiv.org/abs/1805.00249v1","url_pdf":"http://arxiv.org/pdf/1805.00249v1.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":"nugget-proposal-networks-for-chinese-event","repo_url":"https://github.com/sanmusunrise/NPNs","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"event-detection","task_name":"Event Detection"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1805.00249","atlas_url":"https://app.syntology.ai/?focus=1805.00249","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}