Word-order Typology in Multilingual BERT: A Case Study in Subordinate-Clause Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3ARV3LXIIW" target="_blank" >RIV/00216208:11320/22:RV3LXIIW - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2022.sigtyp-1.2" target="_blank" >https://aclanthology.org/2022.sigtyp-1.2</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Word-order Typology in Multilingual BERT: A Case Study in Subordinate-Clause Detection
Original language description
The capabilities and limitations of BERT and similar models are still unclear when it comes to learning syntactic abstractions, in particular across languages. In this paper, we use the task of subordinate-clause detection within and across languages to probe these properties. We show that this task is deceptively simple, with easy gains offset by a long tail of harder cases, and that BERT's zero-shot performance is dominated by word-order effects, mirroring the SVO/VSO/SOV typology.
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
2022
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 4th Workshop on Research in Computational Linguistic Typology and Multilingual NLP
ISBN
978-1-955917-93-3
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
11-21
Publisher name
Association for Computational Linguistics
Place of publication
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Event location
Seattle, Washington
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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