Resultados totales (Incluyendo duplicados): 3
Encontrada(s) 1 página(s)
CORA.Repositori de Dades de Recerca
doi:10.34810/data273
Dataset. 2012

FRENCH-SPANISH LMF APERTIUM BILINGUAL DICTIONARY

  • Prompsit Language Engineering, S.L
  • Eleka Ingenieritza Linguistikoa S.L
  • Universitat Pompeu Fabra. Institut Universitari de Lingüística Aplicada (IULA)
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Proyecto: //
DOI: https://doi.org/10.34810/data273
CORA.Repositori de Dades de Recerca
doi:10.34810/data273
HANDLE: https://doi.org/10.34810/data273
CORA.Repositori de Dades de Recerca
doi:10.34810/data273
PMID: https://doi.org/10.34810/data273
CORA.Repositori de Dades de Recerca
doi:10.34810/data273
Ver en: https://doi.org/10.34810/data273
CORA.Repositori de Dades de Recerca
doi:10.34810/data273

CORA.Repositori de Dades de Recerca
doi:10.34810/data287
Dataset. 2012

TERMOTECA

  • Universidade de Vigo. Grupo de investigación TALG
  • Universitat Pompeu Fabra. Institut Universitari de Lingüística Aplicada (IULA)
This lexical resource is the LMF version of the Termoteca, a multilingual terminological database based on the monolingual and parallel speciality texts collected in the corpora of the University of Vigo, namely in the CLUVI Corpus and in the Galician Technical Corpus.

Proyecto: //
DOI: https://doi.org/10.34810/data287
CORA.Repositori de Dades de Recerca
doi:10.34810/data287
HANDLE: https://doi.org/10.34810/data287
CORA.Repositori de Dades de Recerca
doi:10.34810/data287
PMID: https://doi.org/10.34810/data287
CORA.Repositori de Dades de Recerca
doi:10.34810/data287
Ver en: https://doi.org/10.34810/data287
CORA.Repositori de Dades de Recerca
doi:10.34810/data287

CORA.Repositori de Dades de Recerca
doi:10.34810/data356
Dataset. 2012

PANACEA ENVIRONMENT BILINGUAL GLOSSARY FR-EN (FRENCH-ENGLISH)

  • Dublin City University. School of Computing
This folder contains files for bilingual glossary creation from factored phrase tables that include part of speech tagged text for FR-EN language pair. The tables are firstly filtered using part of speech tag sequences for each language so that entries with unsuitable part of speech sequences are filtered out. Then, feature scores from the phrase table are combined in a log-linear model to score each entry. The user specifies how large the output glossary should be (relative to the input) and the bottom ranking entries are discarded to produce the desired size glossary.

Proyecto: //
DOI: https://doi.org/10.34810/data356
CORA.Repositori de Dades de Recerca
doi:10.34810/data356
HANDLE: https://doi.org/10.34810/data356
CORA.Repositori de Dades de Recerca
doi:10.34810/data356
PMID: https://doi.org/10.34810/data356
CORA.Repositori de Dades de Recerca
doi:10.34810/data356
Ver en: https://doi.org/10.34810/data356
CORA.Repositori de Dades de Recerca
doi:10.34810/data356

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