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Error Analysis and the Role of Morphology
University of Copenhagen, Denmark.ORCID iD: 0000-0003-2598-8150
University of Copenhagen, Denmark.
2021 (English)In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics, 2021, p. 1887-1900Conference paper, Published paper (Refereed)
Abstract [en]

We evaluate two common conjectures in error analysis of NLP models: (i) Morphology is predictive of errors; and (ii) the importance of morphology increases with the morphological complexity of a language. We show across four different tasks and up to 57 languages that of these conjectures, somewhat surprisingly, only (i) is true. Using morphological features does improve error prediction across tasks; however, this effect is less pronounced with morphologically complex languages. We speculate this is because morphology is more discriminative in morphologically simple languages. Across all four tasks, case and gender are the morphological features most predictive of error.

Place, publisher, year, edition, pages
2021. p. 1887-1900
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:liu:diva-197945DOI: 10.18653/v1/2021.eacl-main.162OAI: oai:DiVA.org:liu-197945DiVA, id: diva2:1798244
Conference
16th Conference of the European Chapter of the Association for Computational Linguistics, April 19-23, 2021
Available from: 2023-09-18 Created: 2023-09-18 Last updated: 2023-09-26

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Bollmann, Marcel

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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