In this paper we present KIND, an Italian dataset for Named-entity recognition. It contains more than one million tokens with annotation covering three classes: person, location, and organization. The dataset (around 600K tokens) mostly contains manual gold annotations in three different domains (news, literature, and political discourses) and a semi-automatically annotated part. The multi-domain feature is the main strength of the present work, offering a resource which covers different styles and language uses, as well as the largest Italian NER dataset with manual gold annotations. It represents an important resource for the training of NER systems in Italian. Texts and annotations are freely downloadable from the Github repository.
翻译:在本文中,我们介绍的是一个意大利命名实体识别数据集KIND, 它包含100多万个记号,包括三个类别: 个人、地点和组织; 数据集(约600K记号)主要包含三个不同领域的手工黄金说明(新闻、文学和政治论述)和一个半自动附加注释的部分。 多域特征是当前工作的主要力量, 提供了涵盖不同风格和语言使用的资源, 以及意大利最大的带有手工黄金说明的NER数据集。 这是用意大利语培训NER系统的重要资源。 文本和说明可以从 Github 库自由下载。