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Abstracts from the KAS corpus KAS-Abs 2.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko; Erjavec, Tomaž; Fišer, Darja; Ljubešić, Nikola; Ferme, Marko; Borovič, Mladen; Boškovič, Borko; Ojsteršek, Milan; Hrovat, Goran. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
Abstract: The KAS-abs 2.0 corpus contains 125,202 automatically identified Slovenian and/or English abstracts from BSc/BA, MSc/MA, and PhD theses included in the KAS Corpus of Academic Slovene 2.0 (http://hdl.handle.net/11356/1448). The abstracts are either in Slovenian (*-abs-sl.txt, 71,567 files) or English (*-abs-en.txt, 53,635 files); note that some theses have the abstract only in one language. The abstracts are stored in the same manner as the KAS corpus, i.e. as individual files in 1,000 directories, each with the same file identifier suffix. The file with the metadata of the theses is also included. The corpus can be useful for research in e.g. machine translations and terminology extraction, or, using also the full texts from the KAS corpus, for studies in automatic summarisation. Note that there exists the related corpus http://hdl.handle.net/11356/1447, which contains the automatically sentence aligned bi-lingual abstract, and http://hdl.handle.net/11356/1446, which contains a pre-prepared summarization dataset. The corpus is further described in: Žagar, A., Kavaš, M., & Robnik Šikonja, M. (2021). Corpus KAS 2.0: cleaner and with new datasets. In Information Society - IS 2021: Proceedings of the 24th International Multiconference. https://doi.org/10.5281/zenodo.5562228 As opposed to the previous version 1.0, KAS-Abs 2.0 has been extended and most of the errors in abstract identification have been removed, e.g having the Slovene and English abstract in the same file, or the extracted abstracts also containing other parts of the thesis. The metadata file has also been improved, e.g. by giving the theses better CERIF identifiers.
Keyword: abstracts; academic writing; BSc/BA theses; MSc/MA theses; PhD theses
URL: http://hdl.handle.net/11356/1449
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2
The CLASSLA-StanfordNLP model for lemmatisation of standard Slovenian 1.4
Ljubešić, Nikola; Krsnik, Luka. - : Jožef Stefan Institute, 2022
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3
Corpus of academic Slovene KAS 2.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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The Twitter user dataset for discriminating between Bosnian, Croatian, Montenegrin and Serbian Twitter-HBS 1.0
Ljubešić, Nikola; Rupnik, Peter. - : Jožef Stefan Institute, 2022
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Summarization datasets from the KAS corpus KAS-Sum 1.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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Machine Translation datasets from the KAS corpus KAS-MT 1.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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7
ASR training dataset for Croatian ParlaSpeech-HR v1.0
Ljubešić, Nikola; Koržinek, Danijel; Rupnik, Peter. - : Jožef Stefan Institute, 2022
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The news dataset for discriminating between Bosnian, Croatian and Serbian SETimes.HBS 1.0
Ljubešić, Nikola; Rupnik, Peter. - : Jožef Stefan Institute, 2022
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The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian 1.3
Ljubešić, Nikola; Krsnik, Luka. - : Jožef Stefan Institute, 2022
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The GINCO Training Dataset for Web Genre Identification of Documents Out in the Wild ...
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Geographic Adaptation of Pretrained Language Models ...
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The ParlaMint corpora of parliamentary proceedings
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Retweet communities reveal the main sources of hate speech
In: PLoS One (2022)
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The ParlaMint corpora of parliamentary proceedings
In: Lang Resour Eval (2022)
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15
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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Choice of plausible alternatives dataset in Croatian COPA-HR
Ljubešić, Nikola. - : Jožef Stefan Institute, 2021
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Croatian corpus of non-professional written language by typical speakers and speakers with language disorders RAPUT 1.0
Kuvač Kraljević, Jelena; Hržica, Gordana; Štefanec, Vanja. - : Jožef Stefan Institute, 2021. : Faculty of Education and Rehabilitation, University of Zagreb, 2021
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20
The Orange workflow for observing collocation trends ColTrend 1.0
Kosem, Iztok; Krek, Simon; Čibej, Jaka. - : Centre for Language Resources and Technologies, University of Ljubljana, 2021
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