arXiv:2112.15099 공식 코드 · Papers with Code

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

Teresa Paccosi, Alessio Palmero Aprosio

제출 2021-12-30

원문 초록

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.

함께 살펴볼 논문

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arXiv:2504.16007공통 태그 Named Entity Recognition (NER), NER, named-entity-recognition, Named Entity Recognition공식 코드 · Papers with Code

Methods for Recognizing Nested Terms

토론

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