Data-driven dependency parsing of Vedic Sanskrit
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A89ADZUUF" target="_blank" >RIV/00216208:11320/23:89ADZUUF - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147913999&doi=10.1007%2fs10579-023-09636-5&partnerID=40&md5=e544a6c65f3d5abce2be76fe755f4aea" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147913999&doi=10.1007%2fs10579-023-09636-5&partnerID=40&md5=e544a6c65f3d5abce2be76fe755f4aea</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10579-023-09636-5" target="_blank" >10.1007/s10579-023-09636-5</a>
Alternative languages
Result language
angličtina
Original language name
Data-driven dependency parsing of Vedic Sanskrit
Original language description
"This paper describes the first data-driven parser for Vedic Sanskrit, an ancient Indo-Aryan language in which a corpus of important religious and philosophical texts has been composed. We report and critically discuss experiments with the input feature representations, paying special attention to the performance of contextualized word embeddings and to the influence of morpho-syntactic representations on the parsing quality. In addition, we provide an in-depth discussion of the parsing errors that covers structural traits of the predicted trees as well as linguistic and extra-textual influence factors. In its optimal configuration, the proposed model achieves 87.61 unlabeled and 81.84 labeled attachment score on a held-out set of test sentences, demonstrating good performance for an under-resourced language. © 2023, The Author(s)."
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS 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
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
"Language Resources and Evaluation"
ISSN
1574-020X
e-ISSN
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Volume of the periodical
57
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
34
Pages from-to
1173-1206
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85147913999