Error Analysis and the Role of Morphology
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10442219" target="_blank" >RIV/00216208:11320/21:10442219 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Error Analysis and the Role of Morphology
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
ISBN
978-1-954085-02-2
ISSN
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e-ISSN
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Number of pages
14
Pages from-to
1887-1900
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg
Event location
online
Event date
Apr 19, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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