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

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

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

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

NLPnorth

Alexandra Instituttet A/S

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

We present an open-source toolkit for Danish natural language processing (NLP), 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 increase Danish NLP awareness and create a new sentiment-annotated dataset.

Original language	English
Title of host publication	Proceedings of the 23rd Nordic Conference on Computational Linguistics
Publisher	Linköping University Press
Publication date	2021
Pages	460-466
Publication status	Published - 2021

Keywords

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

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https://aclanthology.org/2021.nodalida-main.53.pdf

Cite this

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title = "DaNLP: An open-source toolkit for Danish Natural Language Processing",

abstract = "We present an open-source toolkit for Danish natural language processing (NLP), enabling easy access to Danish NLP{\textquoteright}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 increase Danish NLP awareness and create a new sentiment-annotated dataset.",

keywords = "Danish natural language processing, open-source toolkit, model and dataset wrappers, community building in NLP, sentiment-annotated dataset, Danish natural language processing, open-source toolkit, model and dataset wrappers, community building in NLP, sentiment-annotated dataset",

author = "Pauli, {Amalie Brogaard} and Barrett, {Maria Jung} and Oph{\'e}lie Lacroix and Rasmus Hvingelby",

year = "2021",

language = "English",

pages = "460--466",

booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics",

publisher = "Link{\"o}ping University Press",

}

DaNLP: An open-source toolkit for Danish Natural Language Processing. / Pauli, Amalie Brogaard; Barrett, Maria Jung; Lacroix, Ophélie et al.
Proceedings of the 23rd Nordic Conference on Computational Linguistics. Linköping University Press, 2021. p. 460-466.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

TY - GEN

T1 - DaNLP: An open-source toolkit for Danish Natural Language Processing

AU - Pauli, Amalie Brogaard

AU - Barrett, Maria Jung

AU - Lacroix, Ophélie

AU - Hvingelby, Rasmus

PY - 2021

Y1 - 2021

N2 - We present an open-source toolkit for Danish natural language processing (NLP), 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 increase Danish NLP awareness and create a new sentiment-annotated dataset.

AB - We present an open-source toolkit for Danish natural language processing (NLP), 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 increase Danish NLP awareness and create a new sentiment-annotated dataset.

KW - Danish natural language processing

KW - open-source toolkit

KW - model and dataset wrappers

KW - community building in NLP

KW - sentiment-annotated dataset

KW - Danish natural language processing

KW - open-source toolkit

KW - model and dataset wrappers

KW - community building in NLP

KW - sentiment-annotated dataset

M3 - Article in proceedings

SP - 460

EP - 466

BT - Proceedings of the 23rd Nordic Conference on Computational Linguistics

PB - Linköping University Press

ER -

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

Abstract

Keywords

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