VLSP 2021 - NER Challenge: Named Entity Recognition for Vietnamese

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.
VLSP 2021 - NER挑战:越南命名实体识别
命名实体(NE)是文档中包含人员、组织、地点、时间、数量、电子邮件、电话号码等名称的短语。命名实体识别(NER)是一项基础任务,在许多应用中都很有用,特别是在信息提取和问题回答中。NER上的共享任务提供了多种语言的参考数据集。在2016年和2018年版本的VLSP研讨会系列中,参考NER数据集仅发布了三个主要实体类别:人、组织和地点。在VLSP 2021研讨会上,组织了关于NER的另一个挑战,以处理14个主要实体类型和26个子实体类型的扩展集。本文描述了VLSP 2021评估活动框架下发布的数据集和评估系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信