Cross-Evaluation of Entity Linking and Disambiguation Systems for Clinical Text Annotation

Camilo Thorne, Stefano Faralli, H. Stuckenschmidt
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引用次数: 5

Abstract

In this paper we study whether state-of-the-art techniques for multi-domain and multilingual entity linking can be ported to the clinical domain. To do so, we compare two known entity linking systems, BabelFly and TagMe, that leverage on Wikipedia and DBpedia, with the standard clinical semantic annotation and disambiguation system, MetaMap, over the SemRep clinical word sense disambiguation gold standard. We show that BabelFly and especially TagMe, while achieving decent precision on clinical annotation, outmatch MetaMap's F1-score.
临床文本标注中实体链接和消歧系统的交叉评价
在本文中,我们研究了多领域和多语言实体链接的最新技术是否可以移植到临床领域。为了做到这一点,我们比较了两个已知的实体链接系统,BabelFly和TagMe,它们利用Wikipedia和DBpedia,与标准的临床语义注释和消歧系统MetaMap,在SemRep临床词义消歧的gold标准上。我们表明,BabelFly,尤其是TagMe,在临床注释方面取得了不错的精度,超过了MetaMap的f1得分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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