A Broad-coverage Corpus for Finnish Named Entity Recognition

Jouni Luoma, Miika Oinonen, Maria Pyykönen, Veronika Laippala, Sampo Pyysalo


Abstract
We present a new manually annotated corpus for broad-coverage named entity recognition for Finnish. Building on the original Universal Dependencies Finnish corpus of 754 documents (200,000 tokens) representing ten different genres of text, we introduce annotation marking person, organization, location, product and event names as well as dates. The new annotation identifies in total over 10,000 mentions. An evaluation of inter-annotator agreement indicates that the quality and consistency of annotation are high, at 94.5% F-score for exact match. A comprehensive evaluation using state-of-the-art machine learning methods demonstrates that the new resource maintains compatibility with a previously released single-domain corpus for Finnish NER and makes it possible to recognize named entity mentions in texts drawn from most domains at precision and recall approaching or exceeding 90%. Remaining challenges such as the identification of names in blog posts and transcribed speech are also identified. The newly introduced Turku NER corpus and related resources introduced in this work are released under open licenses via https://turkunlp.org/turku-ner-corpus .
Anthology ID:
2020.lrec-1.567
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4615–4624
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.567
DOI:
Bibkey:
Cite (ACL):
Jouni Luoma, Miika Oinonen, Maria Pyykönen, Veronika Laippala, and Sampo Pyysalo. 2020. A Broad-coverage Corpus for Finnish Named Entity Recognition. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 4615–4624, Marseille, France. European Language Resources Association.
Cite (Informal):
A Broad-coverage Corpus for Finnish Named Entity Recognition (Luoma et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.567.pdf