A Finnish news corpus for named entity recognition.

We present a corpus of Finnish news articles with a manually prepared named entity annotation. The corpus consists of 953 articles (193,742 word tokens) with six named entity classes (organization, location, person, product, event, and date). The articles are extracted from the archives of Digitoday...

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Detalles Bibliográficos
Publicado en:Language Resources & Evaluation Vol. 54; no. 1; pp. 247 - 273
Autores principales: Ruokolainen, Teemu, Kauppinen, Pekka, Silfverberg, Miikka, Lindén, Krister
Formato: Artículo
Publicado: Springer Nature Mar2020
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:We present a corpus of Finnish news articles with a manually prepared named entity annotation. The corpus consists of 953 articles (193,742 word tokens) with six named entity classes (organization, location, person, product, event, and date). The articles are extracted from the archives of Digitoday, a Finnish online technology news source. The corpus is available for research purposes. We present baseline experiments on the corpus using a rule-based and two deep learning systems on two, in-domain and out-of-domain, test sets.