DaCy is a Danish text processing pipeline built using SpaCy. At the time of writing, it has achieved State-of-the-Art performance on part-of-speech (POS) tagging, named-entity recognition (NER) and Dependency parsing for Danish. For an continually updated benchmarkcheck out section on state-of-art.
This website contains the documentation for DaCy as well as an introduction to how to get started using DaCy and its various features.
Where to ask questions?#
To ask report issues or request features, please use the GitHub Issue Tracker. Questions related to SpaCy are kindly referred to the SpaCy GitHub or forum. Otherwise, please use the discussion Forums.
DaCy is a result of great open-source software and contributors. It wouldn’t have been possible without the work by the SpaCy team which developed and integrated the software. Huggingface for developing Transformers and making model sharing convenient. Multiple parties including Certainly.io and Malte Hojmark-Bertelsen for making their models publicly available. Alexandra Institute for developing and maintaining DaNLP which has made it easy to get access to Danish resources and even supplied some of the tagged data themselves.