Towards automatically extracting morphosyntactical error patterns from L1-L2 parallel dependency treebanks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AJI9ZGU59" target="_blank" >RIV/00216208:11320/23:JI9ZGU59 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174523542&partnerID=40&md5=0ee4f09cb3af3192f3c922741ef06c20" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174523542&partnerID=40&md5=0ee4f09cb3af3192f3c922741ef06c20</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Towards automatically extracting morphosyntactical error patterns from L1-L2 parallel dependency treebanks
Original language description
"L1-L2 parallel dependency treebanks are UD-annotated corpora of learner sentences paired with correction hypotheses. Automatic morphosyntactical annotation has the potential to remove the need for explicit manual error tagging and improve interoperability, but makes it more challenging to locate grammatical errors in the resulting datasets. We therefore propose a novel method for automatically extracting morphosyntactical error patterns and perform a preliminary bilingual evaluation of its first implementation through a similar example retrieval task. The resulting pipeline is also available as a prototype CALL application. © 2023 Association for Computational Linguistics."
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
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Proc. Annu. Meet. Assoc. Comput Linguist."
ISBN
978-195942980-7
ISSN
0736-587X
e-ISSN
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Number of pages
13
Pages from-to
585-597
Publisher name
Association for Computational Linguistics (ACL)
Place of publication
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Event location
Singapore
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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