摘要
利用语义角色分析的方法对动态新闻进行事件抽取研究。通过对句子进行论元结构标注,抽取出句子中以谓语动词为中心的论元结构,将其转化为具体的语义角色,并与事件要素进行匹配,完成事件抽取工作。论文提出并重点研究了如何利用Verb Net和Sem Link资源对动词的论元结构与事件要素进行匹配。抽取系统基于该方法对1 000篇新闻语料进行了事件抽取实验,结果表明该方法的F值达到70.6%,具有一定的应用价值。
The event extraction from news on the internet is performed by a method of semantic role analysis.The sentence in the news is annotated with arguments labeler;the argument structures centered with verbs are extracted and converted to a specific semantic role of the verb;and then the semantic roles are matched to the event elements.How to use VerbNet and SemLink resources to match the verb’s arguments and event elements is put forward and studied in detail.The experiment is carried out on1000news corpus crawled from the web,and the results show that the F value is up to70.6%and the proposed method has certain application value.
作者
章顺瑞
骆陈
ZHANG Shunrui;LUO Chen(The Fifth Research Laboratory, The First Engineering Scientific Research Institute of Wuxi,Wuxi Jiangsu 214035,China)
出处
《太赫兹科学与电子信息学报》
2017年第2期279-284,共6页
Journal of Terahertz Science and Electronic Information Technology
关键词
事件抽取
论元结构
语义角色
事件要素
event extraction
arguments structure
semantic role
event elements
