Workflows for kickstarting RBMT in virtually No-Resource Situation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10427162" target="_blank" >RIV/00216208:11320/19:10427162 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/W19-6803" target="_blank" >https://www.aclweb.org/anthology/W19-6803</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Workflows for kickstarting RBMT in virtually No-Resource Situation
Original language description
In this article we describe a work-inprogress best learnt practices on how to start working on rule-based machine translation when working with language that has virtually no pre-existing digital resources for NLP use. We use Karelian language as a case study, in the beginning of our project there were no publically available corpora, parallel or monolingual analysed, no analysers and no translation tools or languagemodels. We show workflows thatwe have find useful to curate and developnecessary NLP resources for thelanguage. Our workflow is aimed also for no-resources working in a sense of no funding and scarce access to native informants, we show that building core NLP resources in parallel can alleviate the problems therein.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů