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.

KIND: an Italian Multi-Domain Dataset for Named Entity Recognition / Paccosi, Teresa; Palmero Aprosio, Alessio. - (2022), pp. 501-507. (Intervento presentato al convegno 13th Conference on Language Resources and Evaluation (LREC 2022) tenutosi a Marseille, France nel 20th-25th June 2022).

KIND: an Italian Multi-Domain Dataset for Named Entity Recognition

Paccosi, Teresa;Palmero Aprosio, Alessio
2022-01-01

Abstract

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.
2022
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Marseille, France
European Language Resources Association (ELRA)
9791095546726
Paccosi, Teresa; Palmero Aprosio, Alessio
KIND: an Italian Multi-Domain Dataset for Named Entity Recognition / Paccosi, Teresa; Palmero Aprosio, Alessio. - (2022), pp. 501-507. (Intervento presentato al convegno 13th Conference on Language Resources and Evaluation (LREC 2022) tenutosi a Marseille, France nel 20th-25th June 2022).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/412719
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