Sharing is Caring: Advantages of Sharing a Language Background with Learners as an Annotator of Learner Data in UD

Caroline Grand-Clement, Arianna Masciolini


Abstract
This paper looks at the impact of annotators sharing a language background with learners when annotating learner data using the Universal Dependencies (UD) framework. We perform a study comparing annotations by two different annotators working on sets of L2 Swedish sentences (learner sentences and target corrections) from the Swedish Learner Language corpus (SweLL) written by learners for whom French is a main writing language. The annotators are both L2 speakers of Swedish but have different knowledge of French: one is a native French speaker and the other has no knowledge of French. We find high annotator agreement, which may indicate an non-significant impact, though we qualitatively observe an advantage in sharing language background.
Anthology ID:
2026.bea-1.35
Volume:
Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026)
Month:
July
Year:
2026
Address:
San Diego, California, USA
Editors:
Ekaterina Kochmar, Bashar Alhafni, Stefano Bannò, Marie Bexte, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Anais Tack, Victoria Yaneva, Zheng Yuan
Venues:
BEA | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
503–512
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URL:
https://preview.aclanthology.org/ingest-acl-workshops/2026.bea-1.35/
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Bibkey:
Cite (ACL):
Caroline Grand-Clement and Arianna Masciolini. 2026. Sharing is Caring: Advantages of Sharing a Language Background with Learners as an Annotator of Learner Data in UD. In Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026), pages 503–512, San Diego, California, USA. Association for Computational Linguistics.
Cite (Informal):
Sharing is Caring: Advantages of Sharing a Language Background with Learners as an Annotator of Learner Data in UD (Grand-Clement & Masciolini, BEA 2026)
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PDF:
https://preview.aclanthology.org/ingest-acl-workshops/2026.bea-1.35.pdf