{"title":"临床文本标注中实体链接和消歧系统的交叉评价","authors":"Camilo Thorne, Stefano Faralli, H. Stuckenschmidt","doi":"10.1145/2993318.2993345","DOIUrl":null,"url":null,"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.","PeriodicalId":177013,"journal":{"name":"Proceedings of the 12th International Conference on Semantic Systems","volume":"143 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Cross-Evaluation of Entity Linking and Disambiguation Systems for Clinical Text Annotation\",\"authors\":\"Camilo Thorne, Stefano Faralli, H. Stuckenschmidt\",\"doi\":\"10.1145/2993318.2993345\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":177013,\"journal\":{\"name\":\"Proceedings of the 12th International Conference on Semantic Systems\",\"volume\":\"143 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th International Conference on Semantic Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2993318.2993345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th International Conference on Semantic Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2993318.2993345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cross-Evaluation of Entity Linking and Disambiguation Systems for Clinical Text Annotation
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.
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