Fantastic Examples and Where to Find Them - Compiling Czech Dataset for Evaluating Dictionary Examples
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F24%3A00137913" target="_blank" >RIV/00216224:14330/24:00137913 - isvavai.cz</a>
Result on the web
<a href="https://raslan2024.nlp-consulting.net/" target="_blank" >https://raslan2024.nlp-consulting.net/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Fantastic Examples and Where to Find Them - Compiling Czech Dataset for Evaluating Dictionary Examples
Original language description
Examples are an important part of a dictionary entry, helping users better understand the word and its usage in context. However, selecting good examples is a challenging and time-consuming task due to varying selection criteria and the vast amount of data to choose from. While different tools have been developed to address this, evaluation remains flawed and lacks standardisation. In this paper, we compile an evaluation dataset for the Czech language, using the GDEX tool and manual annotations to classify examples and explain the classification. Based on our findings, we propose general annotation guidelines to improve consistency. This dataset serves as a foundation for the unified evaluation of dictionary example scoring tools and opens discussion on how to annotate examples. Additionally, we make the dataset publicly available.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Eighteenth Workshop on Recent Advances in Slavonic Natural Languages Processing
ISBN
9788026318354
ISSN
2336-4289
e-ISSN
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Number of pages
10
Pages from-to
37-46
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2024
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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