TitleOne tense per scene: Predicting tense in Chinese conversations
AuthorsGe, Tao
Ji, Heng
Chang, Baobao
Sui, Zhifang
AffiliationKey Laboratory of Computational Linguistics, Ministry of Education, School of EECS, Peking University, Beijing, China
Collaborative Innovation Center for Language Ability, Xuzhou, Jiangsu, China
Computer Science Department, Rensselaer Polytechnic Institute, Troy, NY, United States
Issue Date2015
Publisher53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015
Citation53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015.Beijing, China,2015/1/1,2(668-673).
AbstractWe study the problem of predicting tense in Chinese conversations. The unique challenges include: (1) Chinese verbs do not have explicit lexical or grammatical forms to indicate tense; (2) Tense information is often implicitly hidden outside of the target sentence. To tackle these challenges, we first propose a set of novel sentence-level (local) features using rich linguistic resources and then propose a new hypothesis of 'One tense per scene' to incorporate scene-level (global) evidence to enhance the performance. Experimental results demonstrate the power of this hybrid approach, which can serve as a new and promising benchmark. ? 2015 Association for Computational Linguistics.
URIhttp://hdl.handle.net/20.500.11897/423591
ISSN9781941643730
IndexedEI
Appears in Collections:信息科学技术学院
计算语言学教育部重点实验室

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