Papers by Maria Pyykönen

1 papers
A Broad-coverage Corpus for Finnish Named Entity Recognition (2020.lrec-1)

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Challenge: Named entity recognition (NER) is a fundamental task in natural language processing (NLP).
Approach: They propose to annotate Finnish named entity names using a new corpus built on the Universal Dependencies corpus.
Outcome: The new annotation identifies over 10,000 mentions and maintains compatibility with a previously released single-domain corpus for Finnish NER.

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