{"title":"部分事件共同参考的求值","authors":"J. Araki, E. Hovy, T. Mitamura","doi":"10.3115/v1/W14-2910","DOIUrl":null,"url":null,"abstract":"This paper proposes an evaluation scheme to measure the performance of a system that detects hierarchical event structure for event coreference resolution. We show that each system output is represented as a forest of unordered trees, and introduce the notion of conceptual event hierarchy to simplify the evaluation process. We enumerate the desiderata for a similarity metric to measure the system performance. We examine three metrics along with the desiderata, and show that metrics extended from MUC and BLANC are more adequate than a metric based on Simple Tree Matching.","PeriodicalId":392223,"journal":{"name":"EVENTS@ACL","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Evaluation for Partial Event Coreference\",\"authors\":\"J. Araki, E. Hovy, T. Mitamura\",\"doi\":\"10.3115/v1/W14-2910\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an evaluation scheme to measure the performance of a system that detects hierarchical event structure for event coreference resolution. We show that each system output is represented as a forest of unordered trees, and introduce the notion of conceptual event hierarchy to simplify the evaluation process. We enumerate the desiderata for a similarity metric to measure the system performance. We examine three metrics along with the desiderata, and show that metrics extended from MUC and BLANC are more adequate than a metric based on Simple Tree Matching.\",\"PeriodicalId\":392223,\"journal\":{\"name\":\"EVENTS@ACL\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EVENTS@ACL\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/v1/W14-2910\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EVENTS@ACL","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/v1/W14-2910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper proposes an evaluation scheme to measure the performance of a system that detects hierarchical event structure for event coreference resolution. We show that each system output is represented as a forest of unordered trees, and introduce the notion of conceptual event hierarchy to simplify the evaluation process. We enumerate the desiderata for a similarity metric to measure the system performance. We examine three metrics along with the desiderata, and show that metrics extended from MUC and BLANC are more adequate than a metric based on Simple Tree Matching.