关键词: 实体标注, 在线百科, 命名实体, 实体分类

Abstract: Online encyclopedia entity tagging aims to label online encyclopedia pages with standard named entity tags such as person, location and organization. It is crucial for a wide range of applications such as entity disambiguation, entity relation inference and knowledge base construction and so on. Features of encyclopedia pages can be divided as structure features (e.g., Infobox, title, and category) and content features (i.e., page content). Existing methods that only take one feature or simply combine both features in one classification cause low F1 value. These methods don’t make full use of the difference of these features. This paper presents an online encyclopedia entities tagging method based on page structure and content. This method firstly builds two classifiers with the two kinds of features respectively, and then builds a new classifier by linear combination of these two classifiers, so this method can accurately realize entities tagging. The experimental results show that this method can achieve F1 value improvement over the baseline methods on the task of encyclopedia entity tagging.

Key words: entity tagging, online encyclopedia, named entity, entity classification