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dc.contributor.author Rābante-Buša, Guna
dc.contributor.author Grūzītis, Normunds
dc.contributor.author Bārzdiņš, Guntis
dc.contributor.author Mendes, Afonso
dc.date.accessioned 2024-03-25T12:55:24Z
dc.date.available 2024-03-25T12:55:24Z
dc.date.issued 2022-03
dc.identifier.uri http://hdl.handle.net/20.500.12574/98
dc.description A dataset of hierarchically annotated named entities in Latvian news articles (provided by the Latvian Information Agency LETA) for the development and evaluation of transition-based parsers for named entity recognition (NER).
dc.language.iso lav
dc.publisher AiLab IMCS UL
dc.rights CLARIN ACA
dc.rights.uri https://www.kielipankki.fi/wp-content/uploads/CLARIN_ACA_AFFIL-EDU_NC_NORED_en.html
dc.rights.label ACA
dc.source.uri https://selma-project.eu
dc.subject NER
dc.subject dataset
dc.title SELMA Latvian NER Dataset
dc.type corpus
metashare.ResourceInfo#ContentInfo.mediaType text
has.files yes
branding CLARIN Centre of Latvian language resources and tools
contact.person Normunds Grūzītis normunds.gruzitis@lumii.lv IMCS at University of Latvia
sponsor European Commission 957017 SELMA – Stream Learning for Multilingual Knowledge Transfer euFunds
size.info 741 texts
files.size 1072454
files.count 1


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Vārds
SELMA-NER-LV.zip
Lielums
1.02 MB
Formāts
application/zip
Apraksts
Contains train, dev and test files in a custom data format. For each sentence, every token is annotated with a shift-reduce operation: TRANSITION, SHIFT, REDUCE, or OUT.
MD5
c776d7ccadab859058ac5bcc84ccd00d
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Rādīt vienkāršu vienuma ierakstu