21 to 27 of 27 Results
Mar 26, 2020 -
Pre-trained POS tagging models for German social media
Plain Text - 3.1 KB -
MD5: 1a3740097d932694d280a13ddab6f2f4
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Mar 26, 2020
Rehbein, Ines; Ruppenhofer, Josef; Do, Bich-Ngoc, 2020, "tweeDe", https://doi.org/10.11588/data/S90S35, heiDATA, V1
A German UD Twitter treebank, with >12,000 tokens from 519 tweets, annotated in the Universal Dependencies framework |
Mar 26, 2020 -
tweeDe
Plain Text - 4.3 KB -
MD5: f331fd03061fbc1b28085934d6a9b10f
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Mar 26, 2020 -
tweeDe
Unknown - 945.9 KB -
MD5: 32d20db78b577a921d9fd4bc3868770e
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Jan 20, 2021
van den Berg, Esther; Korfhage, Katharina; Ruppenhofer, Josef; Wiegand, Michael; Markert, Katja, 2020, "German Twitter Titling Corpus", https://doi.org/10.11588/data/AOSUY6, heiDATA, V2, UNF:6:14BxjwJS7Q3mfI6ei7iBBw== [fileUNF]
The German Titling Twitter Corpus consists of 1904 stance-annotated tweets collected in June/July 2018 mentioning 24 German politicians with a doctoral degree. The Addendum contains an additional 296 stance-annotated tweets from each month of 2018 mentioning 10 politicians with a... |
Jan 20, 2021 -
German Twitter Titling Corpus
Tabular Data - 19.7 KB - 5 Variables, 296 Observations - UNF:6:e8JLFj0rmt8hCbrLS38QTg==
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Jan 20, 2021 -
German Twitter Titling Corpus
Markdown Text - 1.2 KB -
MD5: 2fb7128786b3a52452273bb4546963c5
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