Gunlög Sundberg


Learner Corpus Anonymization in the Age of GDPR: Insights from the Creation of a Learner Corpus of Swedish
Beáta Megyesi | Lena Granstedt | Sofia Johansson | Julia Prentice | Dan Rosén | Carl-Johan Schenström | Gunlög Sundberg | Mats Wirén | Elena Volodina
Proceedings of the 7th workshop on NLP for Computer Assisted Language Learning


SweLL on the rise: Swedish Learner Language corpus for European Reference Level studies
Elena Volodina | Ildikó Pilán | Ingegerd Enström | Lorena Llozhi | Peter Lundkvist | Gunlög Sundberg | Monica Sandell
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We present a new resource for Swedish, SweLL, a corpus of Swedish Learner essays linked to learners’ performance according to the Common European Framework of Reference (CEFR). SweLL consists of three subcorpora ― SpIn, SW1203 and Tisus, collected from three different educational establishments. The common metadata for all subcorpora includes age, gender, native languages, time of residence in Sweden, type of written task. Depending on the subcorpus, learner texts may contain additional information, such as text genres, topics, grades. Five of the six CEFR levels are represented in the corpus: A1, A2, B1, B2 and C1 comprising in total 339 essays. C2 level is not included since courses at C2 level are not offered. The work flow consists of collection of essays and permits, essay digitization and registration, meta-data annotation, automatic linguistic annotation. Inter-rater agreement is presented on the basis of SW1203 subcorpus. The work on SweLL is still ongoing with more that 100 essays waiting in the pipeline. This article both describes the resource and the “how-to” behind the compilation of SweLL.