UNESCO’s Proceedings, 1945–2017: A Bilingual Digital Text Corpus
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| Názov: | UNESCO’s Proceedings, 1945–2017: A Bilingual Digital Text Corpus |
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| Autori: | Martin, Benjamin G., Mohammadi Norén, Fredrik, 1984, Mähler, Roger, Marklund, Andreas, Martin, Oriane |
| Zdroj: | Journal of Open Humanities Data. 11:1-5 |
| Predmety: | digital text analysis, international organizations, transnational history, global humanities, text corpus, corpus design |
| Popis: | The record of the meetings of UNESCO’s General Conference offers a valuable resource for research in the global humanities. We present a digital text corpus, including metadata and supplementary material, that makes the complete record of these meetings from 1946 to 2017 in English and/or French accessible in a machine-readable form that is suitable for digital text analysis. The corpus is stored on Zenodo; relevant code is available on GitHub. The corpus offers reuse potential for scholars interested in any of the countless issues that have been discussed and debated in UNESCO’s General Conference over more than seventy years, as well as to Natural Language Processing (NLP) developers interested in the challenges of language recognition and automated segmentation. |
| Popis súboru: | electronic |
| Prístupová URL adresa: | https://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-75744 https://doi.org/10.5334/johd.314 |
| Databáza: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | The record of the meetings of UNESCO’s General Conference offers a valuable resource for research in the global humanities. We present a digital text corpus, including metadata and supplementary material, that makes the complete record of these meetings from 1946 to 2017 in English and/or French accessible in a machine-readable form that is suitable for digital text analysis. The corpus is stored on Zenodo; relevant code is available on GitHub. The corpus offers reuse potential for scholars interested in any of the countless issues that have been discussed and debated in UNESCO’s General Conference over more than seventy years, as well as to Natural Language Processing (NLP) developers interested in the challenges of language recognition and automated segmentation. |
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| ISSN: | 2059481X |
| DOI: | 10.5334/johd.314 |