Linking Text and Knowledge Using the INCEpTION Annotation Platform

Richard Eckart de Castilho, Jan-Christoph Klie, Naveen Kumar, Beto Boullosa, Iryna Gurevych
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引用次数: 9

Abstract

Abstract-In the Digital Humanities (DH), linking text collections to general or domain-specific knowledge bases (KBs) or authority files is important to enable a contextualised analysis. Automatic named entity recognition and entity linking tools require training data or domain-specific methods. Interactive annotation tools do often not support the tasks of entity linking, fact-linking, cross-document reference resolution, etc. We aim to address this gap with the INCEpTION annotation platform, which not only provides these capabilities in the context of a generic annotation tool, but also combines them with machine learning methods to improve annotation efficiency.
使用INCEpTION注释平台链接文本和知识
摘要:在数字人文学科(DH)中,将文本集合链接到一般或特定领域的知识库(KBs)或权威文件对于实现上下文化分析非常重要。自动命名实体识别和实体链接工具需要训练数据或特定于领域的方法。交互式注释工具通常不支持实体链接、事实链接、跨文档引用解析等任务。我们的目标是通过INCEpTION注释平台来解决这一问题,该平台不仅在通用注释工具的背景下提供这些功能,而且还将它们与机器学习方法相结合,以提高注释效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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