{"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/universal-dependencies-parsing-for-colloquial","title":"Universal Dependencies Parsing for Colloquial Singaporean English","arxiv_id":"1705.06463","date":"2017-05-18","proceeding":"ACL 2017 7","authors":["Hongmin Wang","Yue Zhang","GuangYong Leonard Chan","Jie Yang","Hai Leong Chieu"],"abstract":"Singlish can be interesting to the ACL community both linguistically as a\nmajor creole based on English, and computationally for information extraction\nand sentiment analysis of regional social media. We investigate dependency\nparsing of Singlish by constructing a dependency treebank under the Universal\nDependencies scheme, and then training a neural network model by integrating\nEnglish syntactic knowledge into a state-of-the-art parser trained on the\nSinglish treebank. Results show that English knowledge can lead to 25% relative\nerror reduction, resulting in a parser of 84.47% accuracies. To the best of our\nknowledge, we are the first to use neural stacking to improve cross-lingual\ndependency parsing on low-resource languages. We make both our annotation and\nparser available for further research.","url_abs":"http://arxiv.org/abs/1705.06463v1","url_pdf":"http://arxiv.org/pdf/1705.06463v1.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":"universal-dependencies-parsing-for-colloquial","repo_url":"https://github.com/wanghm92/Sing_Par","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"dependency-parsing","task_name":"Dependency Parsing"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1705.06463","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}