CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372188" target="_blank" >RIV/00216208:11320/17:10372188 - isvavai.cz</a>
Result on the web
<a href="http://www.aclweb.org/anthology/K/K17/K17-3001.pdf" target="_blank" >http://www.aclweb.org/anthology/K/K17/K17-3001.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Original language description
The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2017, one of two tasks was devoted to learning dependency parsers for a large number of languages, in a real-world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe data preparation, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
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 CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
ISBN
978-1-945626-70-8
ISSN
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e-ISSN
neuvedeno
Number of pages
19
Pages from-to
1-19
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Vancouver, Canada
Event date
Aug 3, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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