Rapid Ukrainian-English Dictionary Creation Using Post-Edited Corpus Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00131469" target="_blank" >RIV/00216224:14330/23:00131469 - isvavai.cz</a>

Výsledek na webu

<a href="https://elex.link/elex2023/wp-content/uploads/114.pdf" target="_blank" >https://elex.link/elex2023/wp-content/uploads/114.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Rapid Ukrainian-English Dictionary Creation Using Post-Edited Corpus Data

Popis výsledku v původním jazyce

This paper describes the development of a new corpus-based Ukrainian-English dictionary. The dictionary was built from scratch, we used no pre-existing dictionary data. A rapid dictionary development method was used which consists of generating dictionary parts directly from a large corpus, and of post-editing the automatically generated data by native speakers of Ukrainian (not professional lexicographers). The method builds on Baisa et al. (2019) which was improved and updated, and we used a diferent data management model. As the data source, a 3-billion-word Ukrainian web corpus from the TenTen series (Jakubíček et al., 2013) was used. The paper briefy describes the corpus, then we thoroughly explain the individual steps of the miQKiB+ ;2M2`iBQMěTQbi@2/BiBM; workfow, including the volume of the manual work needed for the particular phases in terms of person-days. We also present details about the newly created dictionary and discuss directions for its further development.

Název v anglickém jazyce

Rapid Ukrainian-English Dictionary Creation Using Post-Edited Corpus Data

Popis výsledku anglicky

This paper describes the development of a new corpus-based Ukrainian-English dictionary. The dictionary was built from scratch, we used no pre-existing dictionary data. A rapid dictionary development method was used which consists of generating dictionary parts directly from a large corpus, and of post-editing the automatically generated data by native speakers of Ukrainian (not professional lexicographers). The method builds on Baisa et al. (2019) which was improved and updated, and we used a diferent data management model. As the data source, a 3-billion-word Ukrainian web corpus from the TenTen series (Jakubíček et al., 2013) was used. The paper briefy describes the corpus, then we thoroughly explain the individual steps of the miQKiB+ ;2M2`iBQMěTQbi@2/BiBM; workfow, including the volume of the manual work needed for the particular phases in terms of person-days. We also present details about the newly created dictionary and discuss directions for its further development.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Electronic lexicography in the 21st century (eLex 2023): Invisible Lexicography. Proceedings of the eLex 2023 conference

ISBN

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ISSN

2533-5626

e-ISSN

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Počet stran výsledku

25

Strana od-do

613-637

Název nakladatele

Lexical Computing CZ s.r.o.

Místo vydání

Brno, Czech Republic

Místo konání akce

Brno, Czech Republic

Datum konání akce

1. 1. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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