dc.contributor.author | Terčon, Luka |
dc.contributor.author | Ljubešić, Nikola |
dc.contributor.author | Zdravkova, Katerina |
dc.contributor.author | Erjavec, Tomaž |
dc.date.accessioned | 2023-06-28T14:32:28Z |
dc.date.available | 2023-06-28T14:32:28Z |
dc.date.issued | 2023-06-27 |
dc.identifier.uri | http://hdl.handle.net/11356/1848 |
dc.description | The model for lemmatisation of standard Macedonian was built with the CLASSLA-Stanza tool (https://github.com/clarinsi/classla-stanfordnlp) by training on the 1984 training corpus expanded with the Macedonian SETimes corpus (to be published). The estimated F1 of the lemma annotations is ~98.81. The difference from the previous version is that this version was trained using a larger training dataset. |
dc.language.iso | mkd |
dc.publisher | Jožef Stefan Institute |
dc.relation.isreferencedby | http://dx.doi.org/10.18653/v1/W19-3704 |
dc.relation.replaces | http://hdl.handle.net/11356/1374 |
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 Macedonian 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 | 2295491 |
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- Name
- baseline_lemma_lemmatizer.zip
- Size
- 2.19 MB
- Format
- application/zip
- Description
- Language model
- MD5
- d07d48e0c9f51c18a7c1e4d203c1fd50