@InProceedings{laarmannquante-EtAl:2017:BEA,
  author    = {Laarmann-Quante, Ronja  and  Ortmann, Katrin  and  Ehlert, Anna  and  Vogel, Maurice  and  Dipper, Stefanie},
  title     = {Annotating Orthographic Target Hypotheses in a German L1 Learner Corpus},
  booktitle = {Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {444--456},
  abstract  = {NLP applications for learners often rely on annotated learner corpora. Thereby,
	it is important that the annotations are both meaningful for the task, and
	consistent and reliable. We present a new longitudinal L1 learner corpus for
	German (handwritten texts collected in grade 2--4), which is transcribed and
	annotated with a target hypothesis that strictly only corrects orthographic
	errors, and is thereby tailored to research and tool development for
	orthographic issues in primary school. While for most corpora, transcription
	and target hypothesis are not evaluated, we conducted a detailed
	inter-annotator agreement study for both tasks. Although we achieved high
	agreement, our discussion of cases of disagreement shows that even with
	detailed guidelines, annotators differ here and there for different reasons,
	which should also be considered when working with transcriptions and target
	hypotheses of other corpora, especially if no explicit guidelines for their
	construction are known.},
  url       = {http://www.aclweb.org/anthology/W17-5051}
}