KIND: an Italian Multi-Domain Dataset for Named Entity Recognition
This provides an important resource for training NER systems in Italian, addressing the need for multi-domain coverage in a low-resource language.
The authors introduced KIND, an Italian multi-domain dataset for Named Entity Recognition containing over one million tokens with annotations for person, location, and organization classes, making it the largest Italian NER dataset with manual gold annotations.
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.