One Tense per Scene: Predicting Tense in Chinese Conversations

被引:0
作者
Ge, Tao [1 ,2 ]
Ji, Heng [3 ]
Chang, Baobao [1 ,2 ]
Sui, Zhifang [1 ,2 ]
机构
[1] Peking Univ, Sch EECS, Minist Educ, Key Lab Computat Linguist, Beijing 100871, Peoples R China
[2] Collaborat Innovat Ctr Language Abil, Xuzhou 221009, Jiangsu, Peoples R China
[3] Rensselaer Polytech Inst, Comp Sci Dept, Troy, NY 12180 USA
来源
PROCEEDINGS OF THE 53RD ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL) AND THE 7TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (IJCNLP), VOL 2 | 2015年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We 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.
引用
收藏
页码:668 / 673
页数:6
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