Czech news dataset for semantic textual similarity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F25%3A10491328" target="_blank" >RIV/00216208:11230/25:10491328 - isvavai.cz</a>
Alternative codes found
RIV/49777513:23520/25:43973860
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=X2vLiEMTgf" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=X2vLiEMTgf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10579-024-09795-z" target="_blank" >10.1007/s10579-024-09795-z</a>
Alternative languages
Result language
angličtina
Original language name
Czech news dataset for semantic textual similarity
Original language description
This paper describes a novel dataset consisting of sentences with two different semantic similarity annotations; with and without surrounding context. The data originate from the journalistic domain in the Czech language. The final dataset contains 138,556 human annotations divided into train and test sets. In total, 485 journalism students participated in the creation process. To increase the reliability of the test set, we compute the final annotations as an average of 9 individual annotation scores. We evaluate the dataset quality by measuring inter and intra-annotator agreements. Besides agreement numbers, we provide detailed statistics of the collected dataset. We conclude our paper with a baseline experiment of building a system for predicting the semantic similarity of sentences. Due to the massive number of training annotations (116,956), the model significantly outperforms an average annotator (0.92 versus 0.86 of Pearson's correlation coefficient).
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
<a href="/en/project/TL02000288" target="_blank" >TL02000288: Transformation of Journalisms Ethics in the Advent of Artificial Intelligence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Language Resources and Evaluation
ISSN
1574-020X
e-ISSN
1574-0218
Volume of the periodical
59
Issue of the periodical within the volume
3
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
18
Pages from-to
1989-2006
UT code for WoS article
001371498800001
EID of the result in the Scopus database
2-s2.0-85211814751