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Refining Border Security News Event Geotagging through Deployment of Lexico-Semantic Patterns

机译:通过部署Lexico语义模式完善边界安全新闻事件的地理标记

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This paper explores a linguistically-oriented method for assigning fine-grained geotagging information to border security-related events reported in online news. It is based on a Cognitive Linguistics model of the semantics of the Locative Prepositional Phrases (LPP) containing place names in news text. We first propose a corpus annotation standard that assigns certain semantic features, such as Locative Relations, to the place names in news articles. Then, based on this, we build a finite state rule-based system that automatically extracts such features and evaluate how they can help discarding implausible event locations. The goal of the experiment is rather a proof of concept that such semantic information can help outperform standard geotagging methods in the border security domain, nonetheless we argument that systems could be built semi-automatically and across languages, based on the proposed annotation standard.
机译:本文探讨了一种针对语言的方法,用于为在线新闻中报道的与边境安全相关的事件分配细粒度的地理标记信息。它基于包含在新闻文本中的地名的位置介词短语(LPP)语义的认知语言学模型。我们首先提出一种语料库注释标准,该标准为新闻文章中的地名分配了某些语义特征,例如“位置关系”。然后,基于此,我们构建了一个基于有限状态规则的系统,该系统会自动提取此类特征并评估它们如何帮助丢弃不合理的事件位置。实验的目的是在概念上证明这样的语义信息可以帮助在边界安全领域中胜过标准地理标记方法,尽管如此,我们认为可以基于提出的注释标准来半自动和跨语言构建系统。

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