News#

2.8.0 (25/08/26): DaCy is Back!#

  • Removed support for python 3.9 and added support for python 3.13

  • Multiple fixes to improve maintainance and long-term support, most notably pipelines are no longer installed into your environment but loaded. Thus some pipelines (e.g. the ones containing coreference models) will require additional optional dependencies (pip install dacy[coref]). dacy.load will let you know if you need optional dependencies for specific models otherwise see installation documentation for more.

2.7.0 (15/05/23)#

  • Updated the DaCy models to version 0.2.0, including a small, medium and large

    • Added beta support for Coreference Resolution! 🤩

    • Added beta support for Named Entity Linking!

    • Updated dependency parsing and part-of-speech tagging to use the latest version of the DDT treebank 🌳

    • Added a trainable lemmatizer, notably improving the lemmatization

    • All model are trained using the intersection between the CDT and the DDT treebanks (so actually trained on less data than before) 🤯

      • This includes the annotations from DaNED, DaCoref and DaNE

  • Large model:

    • obtained state-of-the-art performance on:

      • Dependency parsing

      • Part-of-speech tagging

      • Morphological tagging

      • lemmatization (from 84.91 to 95.89!)

    • Improved performance on:

      • Reduced performance for NER down to 87.38 but we recommend either using the nlp.add_pipe("dacy/ner") to add the SotA ScandiNER model to your pipeline or use one of the new fine-grained NER models.

    • Added support

      • Coreference Resolution, performance isn’t great yet, but it’s a start!

      • Named entity linking, with a precision of 0.86 but recall is still low due to a lacking knowledge base

  • Medium model:

    • Consistent improvements across all tasks:

      • Notable performance gain for NER from an F1 of 81.79 to 85.82

      • Notable performance gain for lemmatization from an ACC 84.91 to 94

    • Added support

      • Coreference Resolution

      • Named entity linking

  • Small model:

    • Consistent improvements across all tasks

    • Added support:

      • Coreference Resolution

      • Named entity linking

  • Fixes a variety of issues:

  • Removed support for DaCy model version 0.1.0, if you need to use these models you will have to use DaCy <= 2.0.0

  • What is next?

    • A coreference resolution only model

    • Better named entity linking by

      • Improving the annotations of DaNED which currently annotate PERSONS using the QID reference to the name among other things

      • Improving the knowledge base which currently is the main source of low recall

    • Examine model generalization using DANSK and whether we can improve the generalization

    • and more!

2.6.0 (10/04/23)#

  • Added support three new models (small, medium, large) for fine-grained NER, which lets you do NER on up to 18 different entities! 🤩

    • You can add these models to your pipeline using nlp.add_pipe("dacy/ner-fine-grained", config={"size": "small"})

2.5.0 (10/04/23)#

  • Removed support for 0.0.0 models. To use these models you will now have to use DaCy=<2.4.3

2.3.0 (05/01/23)#

  • New tutorial added for using DaCy with textdescriptives. You can find it here

2.2.10 (05/01/23)#

  • Added support for spaCy 3.4.0

    • This required the wrapped component model to change name from e.g. dacy.ner to dacy/ner. As the . is no longer allowed by spaCy.

  • Added support for the state-of-the-art NER model by Dan Nielsen

    • You can add this model to your pipeline using nlp.add_pipe("dacy/ner")

2.0.0 (27/06/22): The Spandaur Update#

_images/DALL-E_2022-07-27_A_minimalistic_2d_depiction_of_a_danish_cream_pastry.png

  • Added models for hate-speech detection and classification

  • A large part of DaCy is now moved to seperate packages to allow for more versatility:

    • Now uses spacy-wrap for including existing models in DaCy.

    • Removed augmenters, they are now available through the external package augmenty

    • Removed the rule-based sentiment pipeline instead we recommend using asent

  • Removed support for multiple installs, thus pip install dacy[all] or dacy[large] is no longer required. This should simplify installation processes and avoid errors

  • Documentation

    • New tutorial on using the sentiment models, including emotions detection, subjectivity detection and polarity classifcation.

    • New tutorial on using the hate speech classification and detection.

    • Multiple updated on function and package documentation

  • Multiple bugfixes

1.2.0 (04/11/21)#

  • Removed DaNLP dependency, now DaNLP models is downloaded directly from Huggingface’s model hub which is faster and more stable 🌟.

  • Removed the readability module, we instead recommend you use the more extensive textdescriptives package developed by HLasse and I for extracting readability and other text metrics.

  • Added support for the configuring the default the model location with the environmental variable ‘DACY_CACHE_DIR’ thanks to a PR by dhpullack 🙏.

1.1.0 (23/07/21)#

  • DaCy in now available on the Huggingface model hub 🤗 . Including detailed performance descriptions of biases and robustness.

  • It also got a brand new online demo - try it out!

  • And more, including documentation update and prettier prints.

1.0.0 (09/07/21)#

  • DaCy version 1.0.0 releases as the first version to pypi! 📦

    • Including a series of augmenters with a few specifically designed for Danish

    • Code for behavioural tests of NLP pipelines

    • And new tutorials for both 📖

  • A new beautiful hand-drawn logo 🤩

  • A behavioural test for biases and robustness in Danish NLP pipelines 🧐

  • DaCy is now officially supported by the Centre for Humanities Computing at Aarhus University

  • The first paper on DaCy; check it out as a preprint and code for reproducing it here! 🌟

0.4.1 (03/06/21)#

  • DaCy now has a stunningly looking documentation site 🌟

0.3.1 (01/06/21)#

  • DaCy’s tests now cover 99% of its codebase 🎉

  • DaCy’s test suite is now being applied for all major operating systems instead of just Linux 👩‍💻

0.2.2 (25/05/21)#

  • The new Danish Model Senda was added to DaCy

0.2.1 (30/03/21)#

  • DaCy now includes a small model for efficient processing based on the Danish Ælæctra 🏃

0.1.1 (24/03/21)#

  • DaCy includes a wrapped version of major Danish sentiment analysis software including the models by DaNLP, as well as code for wrapping any sequence classification model into its pipeline 🤩

  • Tutorials is added to introduce the above functionality

0.0.1 (25/02/21)#

  • DaCy launches with a medium-sized and a large language model obtaining state-of-the-art on Named entity recognition, part-of-speech tagging and dependency parsing for Danish 🇩🇰