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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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
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: A Finnish news corpus for named entity recognition.
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          Ruokolainen, Teemu
          Kauppinen, Pekka
          Silfverberg, Miikka
          Lindén, Krister
        affil:
          University of Helsinki, National Library of Finland, Helsinki, Finland
          Department of Modern Languages, University of Helsinki, Helsinki, Finland
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        Corpora
        Attribution of news
        Deep learning
        Instructional systems
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          Corpora
          Attribution of news
          Deep learning
          Instructional systems
      keyword:
        Finnish
        Named entity recognition
        Newswire
        Wikipedia
      ab: 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.
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    language: English
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