Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Annotating Errors in Student Texts: First Experiences and Experiments
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Datorlingvistik)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Datorlingvistik)
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.ORCID iD: 0000-0002-4838-6518
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Scandinavian Languages.
2017 (English)In: Proceedings of Joint 6th NLP4CALL and 2nd NLP4LA Nodalida workshop, Göteborg, 2017, p. 47-60Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Göteborg, 2017. p. 47-60
Keywords [en]
error annotation, student writings
National Category
Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-337518OAI: oai:DiVA.org:uu-337518DiVA, id: diva2:1169891
Conference
Joint 6th NLP4CALL and 2nd NLP4LA Nodalida workshop
Projects
Swe-CLARINAvailable from: 2017-12-30 Created: 2017-12-30 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

fulltext(561 kB)6 downloads
File information
File name FULLTEXT01.pdfFile size 561 kBChecksum SHA-512
0befc7f17cf3417c25bb362190628d177edbcde4185c7ada4bef21a98578e229cb5fdba05e10743b03acadbdbfa66cc2f803fd7ed744ea4c1b8efe1fd7af7d01
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Stymne, SaraPettersson, EvaMegyesi, BeátaPalmér, Anne
By organisation
Department of Linguistics and PhilologyDepartment of Scandinavian Languages
Language Technology (Computational Linguistics)

Search outside of DiVA

GoogleGoogle Scholar
Total: 6 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 18 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf