Universal Dependencies for Learner Russian
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AHQXXS2RL" target="_blank" >RIV/00216208:11320/25:HQXXS2RL - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195993096&partnerID=40&md5=d1128b8139d5db74838cdd9f30383b3e" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195993096&partnerID=40&md5=d1128b8139d5db74838cdd9f30383b3e</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Universal Dependencies for Learner Russian
Original language description
We introduce a pilot annotation of Russian learner data with syntactic dependency relations. The annotation is performed on a subset of sentences from RULEC-GEC and RU-Lang8, two error-corrected Russian learner datasets. We provide manually labeled Universal Dependency (UD) trees for 500 sentence pairs, annotating both the original (source) and the corrected (target) version of each sentence. Further, we outline guidelines for annotating learner Russian data containing non-standard erroneous text and analyze the effect that the individual errors have on the resulting dependency trees. This study should contribute to a wide range of computational and theoretical research directions in second language learning and grammatical error correction. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.
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
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.
ISBN
978-249381410-4
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
17112-17119
Publisher name
European Language Resources Association (ELRA)
Place of publication
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Event location
Torino, Italia
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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