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Data · dataset · 2019

Pretrained word and multi-sense embeddings for Estonian

Listed in DATADOI

Word and multi-sense embedding for Estonian trained on lemmatized etTenTen: Corpus of the Estonian Web.

Description

Word embeddings are trained with word2vec. Sense embeddings are trained with SenseGram.

Sense inventory is induced from word embeddings. Models were trained using various parameter settings. The values of architecture, number of dimensions, window size, minimum frequency threshold and number of iterations vary.

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Where it is published

Catalogue records · 1

Topics

Stated by source
Other
Inferred from text
Lexicography and semantics 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
DATADOIdoi:10.15155/RE-6013 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:field:470408enrichment · datadoi eetaxonomy-embedding@1.1.0title+keywords+description (75%)
concepts[field].dataverse_subject:othersource · datadoi eeconnector:datadoi_ee@1.0.0/subjects
created_datesource · datadoi eeconnector:datadoi_ee@1.0.0
descriptionsource · datadoi eeconnector:datadoi_ee@1.0.0/description
publication_datesource · datadoi eeconnector:datadoi_ee@1.0.0
titlesource · datadoi eeconnector:datadoi_ee@1.0.0/name
updated_datesource · datadoi eeconnector:datadoi_ee@1.0.0
version_labelsource · datadoi eeconnector:datadoi_ee@1.0.0