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Bootstrapping Multilingual Metadata Extraction: A Showcase in Cyrillic
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Data for Cyrillic Reference Parsing ...
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Abstract:
We provide a synthetic reference data set covering over 100,000 labeled references (mostly Russian language) and a manually annotated set of real references (771 in number) gathered from multidisciplinary Cyrillic script publications . Background: Extracting structured data from bibliographic references is a crucial task for the creation of scholarly databases. While approaches, tools, and evaluation data sets for the task exist, there is a distinct lack of support for languages other than English and scripts other than the Latin alphabet. A significant portion of the scientific literature that is thereby excluded consists of publications written in Cyrillic script languages. To address this problem, we introduce a new multilingual and multidisciplinary data set of over 100,000 labeled reference strings. The data set covers multiple Cyrillic languages and contains over 700 manually labeled references, while the remaining are generated synthetically. With random samples of varying size of this data, we train ...
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Keyword:
citation data; citation field extraction; Cyrillic; digital libraries; NLP; references; scholarly data; SDU2022; sequence labeling
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URL: https://zenodo.org/record/5801913 https://dx.doi.org/10.5281/zenodo.5801913
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Data for Training and Evaluating Metadata Extraction Models based on 15 Thousand Cyrillic Script Publications ...
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Data for Training and Evaluating Metadata Extraction Models based on 15 Thousand Cyrillic Script Publications ...
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