Dependency parsing model: Stanza
type: Dataset
description: Models Stanza is currently the default annotation tool used by Sparv. We provide two models that enable dependency parsing of Swedish (in the Mamba-Dep format, the format of TalbankenSBX). stanza_eval is trained on Talbanken_SBX_train with as Talbanken_SBX_dev as dev set and evaluated using Talbanken_SBX_test. The evaluation results are reported in the table below. The LAS (when trained with gold POS and MSD tags) is 84.48. We used the Word2Vec embeddings trained on the CONLL17 corpus (using Word2Vec trained on a Göteborgs-Posten corpus yields a very similar result of 84.43, see more about embeddings here). stanza_full is trained on Talbanken_SBX_train + Talbanken_SBX_dev with Talbanken_SBX_test as dev set. We cannot evaluate the performance of this model, but we expect it to perform better than stanza_eval, or at least not worse. We updated the "pretrain" file in spring 2025. This was a minor format change. Using the models on your own Unzip the model you want to use and the "pretrain" file (which contains word2vec embeddings encoded in a format required by Stanza). Place the two .pt files in stanza/saved_models/depparse. Run bash scripts/parse.sh UD_Swedish-Talbanken to parse a test set using a pretrained model. The output file will be created in the stanza/corpora folder. If you use other treebank name than UD_Swedish-Talbanken, you would have to rename the model files. The script assumes that the POS tags are already present in the test set. Training your own models Unzip the model you want to use and the "pretrain" file (which contains word2vec embeddings encoded in a format required by Stanza). Follow the instructions provided by Stanza. If you need a pretrained part-of-speech model, you will find it here.
creative work status: completed
  type: DefinedTerm
  in defined term set: http://publications.europa.eu/resource/authority/dataset-status
  term code: COMPLETED
creator: Språkbanken Text
date modified: 2020-12-09
date published: 2024-01-01
language: Swedish
keywords: Natural Language Processing
  type: DefinedTerm
  term code: 10208
keywords: Language Technology (Computational Linguistics)
keywords: model
license: https://creativecommons.org/licenses/by/4.0/
publisher: University of Gothenburg
version: 0

PropertyValue
property ID: DOI
value: 10.23695/WH3Y-2Y24

PropertyValue
property ID: slug
value: stanza_synt

Språkbanken Text
type: Organization

Swedish
type: Language
alternate name: swe

University of Gothenburg
type: Organization