Ha My Linh, Do Duy Dao, Nguyen Thi Minh Huyen, Ngo The Quyen, Doan Xuan Dung
{"title":"VLSP 2021 - NER Challenge: Named Entity Recognition for Vietnamese","authors":"Ha My Linh, Do Duy Dao, Nguyen Thi Minh Huyen, Ngo The Quyen, Doan Xuan Dung","doi":"10.25073/2588-1086/vnucsce.362","DOIUrl":null,"url":null,"abstract":"Named entities (NE) are phrases that contain the names of persons, organizations, locations, times, quantities, email, phone number, etc., in a document. Named Entity Recognition (NER) is a fundamental task that is useful in many applications, especially in information extraction and question answering. Shared tasks on NER provides several reference datasets in many languages. In the 2016 and 2018 editions of the VLSP workshop series, reference NER datasets have been published with only three main entity categories: person, organization and location. At the VLSP 2021 workshop, another challenge on NER is organized for dealing with an extended set of 14 main entity types and 26 sub-entity types. This paper describes the published datasets and the evaluated systems in the framework of the VLSP 2021 evaluation campaign.","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"VNU Journal of Science: Computer Science and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25073/2588-1086/vnucsce.362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Named entities (NE) are phrases that contain the names of persons, organizations, locations, times, quantities, email, phone number, etc., in a document. Named Entity Recognition (NER) is a fundamental task that is useful in many applications, especially in information extraction and question answering. Shared tasks on NER provides several reference datasets in many languages. In the 2016 and 2018 editions of the VLSP workshop series, reference NER datasets have been published with only three main entity categories: person, organization and location. At the VLSP 2021 workshop, another challenge on NER is organized for dealing with an extended set of 14 main entity types and 26 sub-entity types. This paper describes the published datasets and the evaluated systems in the framework of the VLSP 2021 evaluation campaign.