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

Title:

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

Creator:

Estève, Louis Clément, Savary, Agata, and Lavergne, Thomas

Contributor:

Université Paris Saclay@@Plan blanc@@PhD grant@@nationalFunds@@

Publisher:

Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique

Identifier:

http://hdl.handle.net/11234/1-5528

Subject:

verbal multiword expressions, word embeddings, and word2vec

Type:

text, computationalLexicon, and lexicalConceptualResource

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.

Language:

German, Modern Greek (1453-), Basque, French, Irish, Hebrew, Hindi, Italian, Polish, Portuguese, Romanian, Swedish, Turkish, and Chinese

Rights:

PARSEME Shared Task Raw Corpus Data (v. 1.2) Agreement
https://lindat.mff.cuni.cz/repository/xmlui/page/licence-mwe-1.2-raw
PUB

Source:

https://gitlab.com/parseme/corpora

Harvested from:

LINDAT/CLARIAH-CZ repository

Metadata only:

false

Date:

2024-06-07