Pablo Barrio, Gonçalo Simões, H. Galhardas, L. Gravano
{"title":"REEL:一个关系抽取学习框架","authors":"Pablo Barrio, Gonçalo Simões, H. Galhardas, L. Gravano","doi":"10.1109/JCDL.2014.6970222","DOIUrl":null,"url":null,"abstract":"We introduce the REEL (RElation Extraction Learning) framework, an open source framework that facilitates the development and evaluation of relation extraction systems over text collections. To define a relation extraction system for a new relation and text collection, users only need to specify the parsers to load the collection, the relation and its constraints, and the learning and extraction techniques to be used. This makes REEL a powerful framework to enable the deployment and evaluation of relation extraction systems for both application building and research.","PeriodicalId":92278,"journal":{"name":"Proceedings of the ... ACM/IEEE Joint Conference on Digital Libraries. ACM/IEEE Joint Conference on Digital Libraries","volume":"7 1","pages":"455-456"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"REEL: A Relation Extraction Learning framework\",\"authors\":\"Pablo Barrio, Gonçalo Simões, H. Galhardas, L. Gravano\",\"doi\":\"10.1109/JCDL.2014.6970222\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce the REEL (RElation Extraction Learning) framework, an open source framework that facilitates the development and evaluation of relation extraction systems over text collections. To define a relation extraction system for a new relation and text collection, users only need to specify the parsers to load the collection, the relation and its constraints, and the learning and extraction techniques to be used. This makes REEL a powerful framework to enable the deployment and evaluation of relation extraction systems for both application building and research.\",\"PeriodicalId\":92278,\"journal\":{\"name\":\"Proceedings of the ... ACM/IEEE Joint Conference on Digital Libraries. ACM/IEEE Joint Conference on Digital Libraries\",\"volume\":\"7 1\",\"pages\":\"455-456\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... ACM/IEEE Joint Conference on Digital Libraries. ACM/IEEE Joint Conference on Digital Libraries\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JCDL.2014.6970222\",\"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 ... ACM/IEEE Joint Conference on Digital Libraries. ACM/IEEE Joint Conference on Digital Libraries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JCDL.2014.6970222","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We introduce the REEL (RElation Extraction Learning) framework, an open source framework that facilitates the development and evaluation of relation extraction systems over text collections. To define a relation extraction system for a new relation and text collection, users only need to specify the parsers to load the collection, the relation and its constraints, and the learning and extraction techniques to be used. This makes REEL a powerful framework to enable the deployment and evaluation of relation extraction systems for both application building and research.