Corpus-based Syntactic Typological Methods for Dependency Parsing Improvement
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10476178" target="_blank" >RIV/00216208:11320/23:10476178 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2023.sigtyp-1.8" target="_blank" >https://aclanthology.org/2023.sigtyp-1.8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2023.sigtyp-1.8" target="_blank" >10.18653/v1/2023.sigtyp-1.8</a>
Alternative languages
Result language
angličtina
Original language name
Corpus-based Syntactic Typological Methods for Dependency Parsing Improvement
Original language description
This article presents a comparative analysis of four different syntactic typological approaches applied to 20 different languages to determine the most effective one to be used for the improvement of dependency parsing results via corpus combination. We evaluated these strategies by calculating the correlation between the language distances and the empirical LAS results obtained when languages were combined in pairs. From the results, it was possible to observe that the best method is based on the extraction of word order patterns which happen inside subtrees of the syntactic structure of the sentences.
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
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
Proceedings of the 5th Workshop on Research in Computational Linguistic Typology and Multilingual NLP
ISBN
978-1-959429-56-2
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
76-88
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Dubrovnik, Croatia
Event date
May 2, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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