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When Word Pairs Matter - Analysis of the English-Slovak Evaluation Dataset

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F21%3A00123252" target="_blank" >RIV/00216224:14330/21:00123252 - isvavai.cz</a>

  • Result on the web

    <a href="https://nlp.fi.muni.cz/raslan/2021/paper3.pdf" target="_blank" >https://nlp.fi.muni.cz/raslan/2021/paper3.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    When Word Pairs Matter - Analysis of the English-Slovak Evaluation Dataset

  • Original language description

    Cross-lingual word embeddings facilitate the transfer of lexical knowledge across languages, and they are mainly used for finding transla- tion equivalents. Translation equivalents obtained in this way are usually evaluated with the help of ground truth dictionaries. However, the evalu- ation process, including the ground truth dictionaries, differs from model to model, impeding the correct interpretation of the results. Therefore, in this paper, we provide a thorough analysis of the English-Slovak ground truth dictionary and employ our analysis in evaluating two cross-lingual word embedding models. We show that word pairs choice is an important factor when accurately reflecting the model’s performance.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

    <a href="/en/project/LM2018101" target="_blank" >LM2018101: Digital Research Infrastructure for the Language Technologies, Arts and Humanities</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)

  • ISBN

    9788026316701

  • ISSN

    2336-4289

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    141-149

  • Publisher name

    Tribun EU

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Jan 1, 2021

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article