Cross-lingual Adaptation Using Universal Dependencies
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441595" target="_blank" >RIV/00216208:11320/21:10441595 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=dZhh3n11ec" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=dZhh3n11ec</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3448251" target="_blank" >10.1145/3448251</a>
Alternative languages
Result language
angličtina
Original language name
Cross-lingual Adaptation Using Universal Dependencies
Original language description
We describe a cross-lingual adaptation method based on syntactic parse trees obtained from the Universal Dependencies (UD), which are consistent across languages, to develop classifiers in low-resource languages. The idea of UD parsing is to capture similarities as well as idiosyncrasies among typologically different languages. In this article, we show that models trained using UD parse trees for complex NLP tasks can characterize very different languages. We study two tasks of paraphrase identification and relation extraction as case studies. Based on UD parse trees, we develop several models using tree kernels and show that these models trained on the English dataset can correctly classify data of other languages, e.g., French, Farsi, and Arabic. The proposed approach opens up avenues for exploiting UD parsing in solving similar cross-lingual tasks, which is very useful for languages for which no labeled data is available.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
Name of the periodical
ACM Transactions on Asian and Low-Resource Language Information Processing
ISSN
2375-4699
e-ISSN
2375-4702
Volume of the periodical
20
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
23
Pages from-to
65
UT code for WoS article
000721582900012
EID of the result in the Scopus database
2-s2.0-85111026083