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dc.contributor.author Terčon, Luka
dc.contributor.author Ljubešić, Nikola
dc.date.accessioned 2023-05-16T06:50:00Z
dc.date.available 2023-05-16T06:50:00Z
dc.date.issued 2023-05-10
dc.identifier.uri http://hdl.handle.net/11356/1832
dc.description The model for morphosyntactic annotation of standard Croatian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the hr500k training corpus (http://hdl.handle.net/11356/1792) and using the CLARIN.SI-embed.hr word embeddings (http://hdl.handle.net/11356/1790). The model produces simultaneously UPOS, FEATS and XPOS (MULTEXT-East) labels. The estimated F1 of the XPOS annotations is ~94.87. The difference to the previous version of the model is that this version was trained using the new version of the hr500k corpus and the new version of the Croatian word embeddings.
dc.language.iso hrv
dc.publisher Jožef Stefan Institute
dc.relation.isreferencedby http://dx.doi.org/10.18653/v1/W19-3704
dc.relation.replaces http://hdl.handle.net/11356/1348
dc.rights Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
dc.rights.uri https://creativecommons.org/licenses/by-sa/4.0/
dc.rights.label PUB
dc.source.uri https://github.com/clarinsi/classla
dc.subject language model
dc.subject part-of-speech tagging
dc.title The CLASSLA-Stanza model for morphosyntactic annotation of standard Croatian 2.1
dc.type toolService
metashare.ResourceInfo#ContentInfo.detailedType tool
metashare.ResourceInfo#ResourceComponentType#ToolServiceInfo.languageDependent true
has.files yes
branding CLARIN.SI data & tools
contact.person Nikola Ljubešić nikola.ljubesic@ijs.si Jožef Stefan Institute
contact.person Luka Terčon luka.tercon@gmail.com Faculty of Computer and Information Science, University of Ljubljana
sponsor ARRS (Slovenian Research Agency) P6-0411 Language Resources and Technologies for Slovene nationalFunds
sponsor Jožef Stefan Institute CLARIN CLARIN.SI nationalFunds
sponsor ARRS (Slovenian Research Agency) J7-4642 MEZZANINE nationalFunds
sponsor Connecting Europe Facility (CEF) Telecom INEA/CEF/ICT/A2020/2278341 MaCoCu - Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages Other
files.count 2
files.size 185620047


 Datoteke v tem vnosu

 Prenesi vse datoteke v vnosu (177.02 MB)
Icon
Ime
baseline_pos.zip
Velikost
71.68 MB
Format
application/zip
Opis
Language model
MD5
0dbefd95b263c269a5e01215f19112c9
 Prenesi datoteko  Predogled
 Predogled datoteke  
    • baseline_pos76 MB
Icon
Ime
hr_set.pretrain.zip
Velikost
105.34 MB
Format
application/zip
Opis
Pretrained word embeddings
MD5
49951c88b928436128dad24d68168f88
 Prenesi datoteko  Predogled
 Predogled datoteke  
    • hr_set.pretrain.pt150 MB

Prikaži enostavni zapis vnosa