DaNLP: An open-source toolkit for Danish Natural Language Processing

Amalie Brogaard Pauli, Maria Jung Barrett, Ophélie Lacroix, Rasmus Hvingelby

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Abstract

We present an open-source toolkit for Danish Natural Language Processing, enabling easy access to Danish NLP’s latest advancements. The toolkit features wrapper-functions for loading models and datasets in a unified way using third-party NLP frameworks. The toolkit is developed to enhance community building, understanding the need from industry and knowledge sharing. As an example of this, we present Angry Tweets: An Annotation Game to create awareness of Danish NLP and create a new sentiment-annotated dataset.
OriginalsprogEngelsk
TitelProceedings of the 23rd Nordic Conference on Computational Linguistics
ForlagLinköping Electronic Conference Proceedings
Publikationsdato2021
Sider460-466
StatusUdgivet - 2021

Emneord

  • Danish natural language processing
  • open-source toolkit
  • model and dataset wrappers
  • community building in NLP
  • sentiment-annotated dataset

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