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A Finnish News Corpus for Named Entity Recognition

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arxiv 1908.04212 v1 pith:GLY2JMAJ submitted 2019-08-12 cs.CL

Teemu Ruokolainen , Pekka Kauppinen , Miikka Silfverberg , Krister Lindén This is my paper · ORCID
classification cs.CL
keywords corpusarticlesentityfinnishnamednewsannotationarchives
verification ladder T0 review T1 audit T2 compute T3 formal
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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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