Error analysis and the role of morphology
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Dokumenter
- Error Analysis and the Role of Morphology
Forlagets udgivne version, 648 KB, PDF-dokument
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.
Originalsprog | Engelsk |
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Titel | EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference |
Forlag | Association for Computational Linguistics |
Publikationsdato | 2021 |
Sider | 1887-1900 |
ISBN (Elektronisk) | 9781954085022 |
Status | Udgivet - 2021 |
Begivenhed | 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021 - Virtual, Online Varighed: 19 apr. 2021 → 23 apr. 2021 |
Konference
Konference | 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021 |
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By | Virtual, Online |
Periode | 19/04/2021 → 23/04/2021 |
Sponsor | Babelscape, Bloomberg Engineering, Facebook AI, Grammarly, LegalForce |
Links
- https://aclanthology.org/2021.eacl-main.162/
Forlagets udgivne version
ID: 283136052