VLSP 2021 - NER挑战:越南命名实体识别

Ha My Linh, Do Duy Dao, Nguyen Thi Minh Huyen, Ngo The Quyen, Doan Xuan Dung
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引用次数: 1

摘要

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。
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VLSP 2021 - NER Challenge: Named Entity Recognition for Vietnamese
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.
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