Annotating Errors in Student Texts: First Experiences and Experiments

We describe the creation of an annotation layer for word-based writing errors for a corpus of student writings. The texts are written in Swedish by students between 9 and 19 years old. Our main purpose is to identify errors regarding spelling, split compounds and merged words. In addition, we also identify simple word-based grammatical errors, including morphological errors and extra words. In this paper we describe the corpus and the annotation process, including detailed descriptions of the error types and guidelines. We find that we can perform this annotation with a substantial inter-annotator agreement, but that there are still some remaining issues with the annotation. We also report results on two pilot experiments regarding spelling correction and the consistency of downstream NLP tools, to exemplify the usefulness of the annotated corpus.