A Finnish News Corpus for Named Entity Recognition

12 Aug 2019  ·  Teemu Ruokolainen, Pekka Kauppinen, Miikka Silfverberg, Krister Lindén ·

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.

PDF Abstract

Datasets


Introduced in the Paper:

Finer

Used in the Paper:

CoNLL 2003

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here