Non-Entity Event Argument Extraction on Structural Representation
被引:0
|
作者:
Liu, Yiting
论文数: 0引用数: 0
h-index: 0
机构:
Soochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R ChinaSoochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R China
Liu, Yiting
[1
]
Li, Peifeng
论文数: 0引用数: 0
h-index: 0
机构:
Soochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R ChinaSoochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R China
Li, Peifeng
[1
]
机构:
[1] Soochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R China
来源:
2017 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP)
|
2017年
关键词:
non-entity event argument extraction;
structural representation;
minimum common tree;
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:
Currently almost all work of event argument extraction focused on extracting entity-based arguments. However, non-entity arguments also play an important semantic role in most events; Inspired by the task of speculation and negation scope detection, this paper proposes a novel structural representation-based method to extract those non-entity arguments, which regards the selected syntactic subtrees of a sentence as the candidates of non-entity arguments and directly explores the syntactic relations between the event triggers and the syntactic subtrees to recognize nonentity arguments. The experimental results show that our method improves PCS by 12.6%, compared to the baseline.