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...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Ruokolainen, Teemu, Kauppinen, Pekka, Silfverberg, Miikka, Lindén, Krister
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 01.03.2020
Subjects
Annotations
Computer Science - Computation and Language
Machine learning
News
Test sets
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.1908.04212