基于新闻事件片段的时序关系识别方法

doi:10.11959/j.issn.2096-109x.2017.00171

Abstract

CLC Number:

TP393

Ying-jun LI,Hong-li ZHANG,Xing WANG. Temporal relation recognition method based on news event fragments[J]. Chinese Journal of Network and Information Security, 2017, 3(6): 33-41.

Figures/Tables 9

References 27

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序号	例句
例1	……「今天，由中国贸易促进会广东分会与香港中华总商会联合主办的“九六税改及进口原料台账制执行实务研讨会在广州举行，向客商介绍「今年国家将实行的外经贸三大政策调整。」」……
例2	近年来，江苏省在对外开放中下大力气进一步改善投资环境，获得重大进展，增强了对外商投资的吸引力
例3	美、英、法三国的士兵也将于9月初最后撤离柏林。德国领土上存在占领军的状态行将结束

关系	描述
Before	tsi先于tsj发生
After	tsi后于tsj发生
Overlap	tsi和tsj的发生持续时间有交叉
Include	tsi的发生持续时间区间包含tsj
Simultaneous	tsi和tsj同时发生
None	tsi和tsj时序关系未知

特征编号	描述
①	2个句子之间是否存在时间词，存在：exist_t = 1；不存在：exist_t = 0
②	2个句子之间是否存在转折词，存在：exist_tr = 1；不存在：exist_tr = 0
③	2个句子中间间隔句子数，句子数：num
④	2个句子是否有时间功能词连接，存在：exist_f = 1；不存在：exist_f = 0
⑤	2个句子先后顺序，先于：order = b 后于：order = a

特征类别	具体特征
语义特征	2个事件片段核心词的语义相似度，用sim表示
	2个事件片段核心词是否为同义，用if_syn表示
	时间区间是否是DCT，用if_dct表示
特殊词	时间区间先后顺序，用order_t表示
	时间区间时态信息先后，用order_tense
	2个事件片段之间是否存在连接词，用if_conj表示
上下文信息	2 个事件片段在文中出现的先后顺序，用 order_a表示
	2个事件片段是否在同一个句子中，用if_in表示
	2个事件片段间隔的句子数目，用num表示

特殊词	时间区间
春节	过年的7天
五四	5月4日
六一	6月1日
圣诞节	12月24日至12月26日
国庆节	10月1日至10月7日

Temporal relation recognition method based on news event fragments

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Figures/Tables 9

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方法	P	R	F1
方法一	72.2%	72.34%	72.27%
方法二	73.31%	73.41%	73.36%
方法三	74.19%	74.32%	74.25%
本文方法	79.76%	80.01%	79.88%

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