Summary

A treebank of learner Swedish based on SweLL, the Swedish Learner Language corpus.

Introduction

UD_Swedish-SweLL is a parallel learner treebank based on SweLL, the Swedish Learner Language corpus.

As of it first release, UD_Swedish-SweLL consists of a test set comprising 510 randomly selected sentences from SweLL-gold, a corpus of essays written by adult learners of Swedish as a second language (L2). All essays in SweLL-gold are manually pseudonymized, error-labelled and normalized, i.e. accompanied by a correction hypothesis. While the official UD 2.17 release only includes original learner sentences, such corrections are available in the not-to-release folder of this repository.

Annotation

Each sentence-correction pair was pre-annotated with UDPipe 2 using the swedish-talbanken-ud-2.15-241121 model. The resulting annotations underwent extensive manual post-correction. Each pair was edited by two annotators, who are themselves L2 Swedish speakers and worked in parallel, meeting periodically to resolve disagreements.

In particular:

• lemmas, UPOS tags and dependencies were checked systematically
• morphological features were only checked for tokens marked as learner errors in the source corpus and/or whose automatic lemmatization, POS tagging and/or dependency annotation were found to be incorrect
• SweLL-gold error labels, documented here, are included in the MISC column and were used to automatically assign the Typo=Yes feature to tokens presenting orthography errors.

The general annotation principles for the annotation of interlanguage phenomena are as follows:

• token-level annotation (lemmatization, POS tagging and morphological analysis) should be purely descriptive of the observed word forms__ (also referred to as literal)
• dependency annotation should also be as descriptive of the observed language use as possible, but grounded in the correction hypothesis of the sentence whenever different interpretations of the learner's intended meaning would lead to different analyses. This is to ensure comparability between learner productions and their corrections
• in general, annotation should be aware of transfer phenomena.

For a more comprehensive discussion of these principles, see Annotating Second Language in Universal Dependencies: a Review of Current Practices and Directions for Harmonized Guidelines (Masciolini et al., UDW-SyntaxFest 2025), as well as the annotation guidelines for UD_Swedish-SweLL, available in the not-to-release folder.

In rare occasions (6 tokens), these principles clash with current UD validation rules. When this was the case, annotation was adjusted to comply with the general guidelines and the annotator's preferred analysis was moved to the MISC column under the key IntendedXXX (at the moment, only IntendedDeprel and IntendedLemma are attested). This is, however, a temporary workaround pending a community discussion.

Metadata

SweLL-gold comes with rich learner metadata that cannot be redistributed in full due to licensing restrictions. We currently include:

• l1: the first language(s) of the author of the essay*
• approximate_level: Nybörjare (beginner), Fortsättning (intermediate) or Avancerad (advanced)
• writing_language: the language in which the author of the essay has better written proficiency*
• sent_id: the sentence ID, whose format is org-N-test for original learner productions and trg-N-test for the corresponding correction hypotheses (N is a sequential ID)
• text: the full text of the sentence (pre-tokenized)

*in Swedish, planned to be replaced with ISO codes

Acknowledgments

The manual annotation work has been carried out by Arianna Masciolini, Aleksandrs Berdicevskis and Maria Irena Szawerna, who thank Elena Volodina for her work on the source corpus, as well as for her participation in the initial UD annotation experiments.

This work is funded by the Swedish national research infrastructure Språkbanken, jointly financially supported by the Swedish Research Council (2025–2028; grant 2023-00161) and the 10 participating partner institutions. It received further support by the CA21167 COST action UniDive, funded by COST (European Cooperation in Science and Technology).

Contributing

If you spot any annotation errors or inconsistencies, please open an issue in this repository.

For practical and legal reason, however, the annotation work is carried out in a private repository where we have access to all learner metadata. If you want to get involved, you are much welcome get in touch with the treebank's maintainer at [email protected].

References

A paper describing UD_Swedish-SweLL in detail is currently in preparation. Meanwhile, if you use the treebank in you work, you are encouraged to cite SweLL with pride: How to put a learner corpus to good use (Volodina et al., Huminfra Handbook - forthcoming):

@article{swell_with_pride,
  title        = {{SweLL} with pride: How to put a learner corpus to good use},
  author       = {Volodina, Elena and Masciolini, Arianna and Megyesi, Beáta and Prentice, Julia and Rudebeck, Lisa and Sundberg, Gunlög and Wirén, Mats},
  year         = 2025,
  journal      = {Huminfra Handbook (forthcoming)},
}

For more up-to-date citation information, check out the dev branch of this repository.

Changelog

• 2025-11-15 v2.17
  • Initial release in Universal Dependencies.

=== Machine-readable metadata (DO NOT REMOVE!) ================================
Data available since: UD v2.17
License: CC BY-SA 4.0
Includes text: yes
Parallel: no
Genre: learner-essays
Lemmas: manual native
UPOS: manual native
XPOS: not available
Features: automatic with corrections
Relations: manual native
Contributors: Masciolini, Arianna; Berdicevskis, Aleksandrs; Szawerna, Maria Irena
Contributing: elsewhere
Contact: [email protected]
===============================================================================