Multilingual static embeddings for Verbal Multiword Expressions trained on PARSEME raw corpora

 
LINDAT / CLARIAH-CZ
  Authors
Estève, Louis Clément ; Savary, Agata and Lavergne, Thomas
  Item identifier
http://hdl.handle.net/11234/1-5528
 Project URL
https://gitlab.com/parseme/corpora
 Date issued
2024-06-07
 Type
lexicalConceptualResource, text
 Size
44412316 entries, 17267 multiWordUnits
 Language(s)
Basque , Chinese , French , German , Hebrew , Hindi , Irish , Italian , Modern Greek (1453-) , Polish , Portuguese , Romanian , Swedish , Turkish
 Description
This resource is a set of 14 vector spaces for single words and Verbal Multiword Expressions (VMWEs) in different languages (German, Greek, Basque, French, Irish, Hebrew, Hindi, Italian, Polish, Brazilian Portuguese, Romanian, Swedish, Turkish, Chinese). They were trained with the Word2Vec algorithm, in its skip-gram version, on PARSEME raw corpora automatically annotated for morpho-syntax (http://hdl.handle.net/11234/1-3367). These corpora were annotated by Seen2Seen, a rule-based VMWE identifier, one of the leading tools of the PARSEME shared task version 1.2. VMWE tokens were merged into single tokens. The format of the vector space files is that of the original Word2Vec implementation by Mikolov et al. (2013), i.e. a binary format. For compression, bzip2 was used.
 Publisher
Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique
 Acknowledgement

Université Paris Saclay

Project code: Plan blanc

Project name: PhD grant

 Subject(s)
verbal multiword expressions word embeddings word2vec
 Collection(s)
LINDAT / CLARIAH-CZ Data & Tools
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 Files in this item

This item is
Publicly Available
and licensed under:
PARSEME Shared Task Raw Corpus Data (v. 1.2) Agreement
Distributed under Creative Commons
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