The CLASSLA-Stanza model for lemmatisation of standard Croatian 2.1

Name: The CLASSLA-Stanza model for lemmatisation of standard Croatian 2.1
License: https://creativecommons.org/licenses/by-sa/4.0/

Terčon, Luka; Ljubešić, Nikola

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dc.contributor.author	Terčon, Luka
dc.contributor.author	Ljubešić, Nikola
dc.date.accessioned	2023-05-16T06:52:24Z
dc.date.available	2023-05-16T06:52:24Z
dc.date.issued	2023-05-10
dc.identifier.uri	http://hdl.handle.net/11356/1829
dc.description	The model for lemmatisation 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 hrLex inflectional lexicon (http://hdl.handle.net/11356/1232). The estimated F1 of the lemma annotations is ~98.02. The difference to the previous version is that this version was trained on the new version of the hr500k corpus.
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/11356/1357
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	lemmatisation
dc.subject	language model
dc.title	The CLASSLA-Stanza model for lemmatisation 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	1
files.size	102900658