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dc.contributor.author Terčon, Luka
dc.contributor.author Ljubešić, Nikola
dc.contributor.author Osenova, Petya
dc.contributor.author Simov, Kiril
dc.date.accessioned 2023-06-29T05:52:29Z
dc.date.available 2023-06-29T05:52:29Z
dc.date.issued 2023-06-27
dc.identifier.uri http://hdl.handle.net/11356/1851
dc.description The model for UD dependency parsing of standard Bulgarian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla) by training on the UD-parsed portion of the BulTreeBank training corpus (https://clarino.uib.no/korpuskel/corpora) and using the CLARIN.SI-embed.bg word embeddings (http://hdl.handle.net/11356/1796). The estimated LAS of the parser is ~91.18. The difference to the previous version of the parser is that this version was trained using the new version of the Bulgarian word embeddings.
dc.language.iso bul
dc.publisher Jožef Stefan Institute
dc.publisher IICT-BAS
dc.relation.isreferencedby http://dx.doi.org/10.18653/v1/W19-3704
dc.relation.replaces http://hdl.handle.net/11356/1328
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 parsing
dc.subject language model
dc.title The CLASSLA-Stanza model for UD dependency parsing of standard Bulgarian 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 Ministry of Education and Science Republic of Bulgaria DO01-272/16.12.2019 Bulgarian National Interdisciplinary Research e-Infrastructure for Resources and Technologies CLaDA-BG 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 199927180


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