  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.
