11 to 20 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; Zimmermann, Victor, 2020, "A harmonised testsuite for social media POS tagging (DE)", https://doi.org/10.11588/data/KXLMHN, heiDATA, V1
A harmonised POS testsuite of web data, CMC and Twitter microtext, with word forms and STTS pos tags (+ some additional CMC-specific tags). UD pos tags have been automatically converted, based on the STTS pos tags. The data does not contain (manually corrected) lemma information.... |
Mar 26, 2020 -
A harmonised testsuite for social media POS tagging (DE)
Unknown - 2.9 MB -
MD5: 8bf35bfb77317b4d789fb0387454f118
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Mar 26, 2020
Rehbein, Ines; Steen, Julius; Do, Bich-Ngoc; Frank, Anette, 2020, "Converter for content-to-head style syntactic dependencies", https://doi.org/10.11588/data/HE3BAZ, heiDATA, V1
A set of Python scripts that convert function-head style encodings in dependency treebanks in a content-head style encoding (as used in the UD treebanks) and vice versa (for adpositions, copula and coordination). For more information, see (Rehbein, Steen, Do & Frank 2017). |
Mar 26, 2020 -
Converter for content-to-head style syntactic dependencies
ZIP Archive - 10.1 MB -
MD5: 30167cb475d743ced8aa63e6349a99ce
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Mar 26, 2020 -
Converter for content-to-head style syntactic dependencies
Plain Text - 1.2 KB -
MD5: fc57366f049837b691c85a50b3e47b46
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Mar 26, 2020
Rehbein, Ines; Ruppenhofer, Josef, 2020, "MACE-AL-TREE", https://doi.org/10.11588/data/THPEBR, heiDATA, V1
An method for detecting noise in automatically annotated dependency parse trees, combining MACE (Hovy et al. 2013) with Active Learning. |
Mar 26, 2020 -
MACE-AL-TREE
ZIP Archive - 141.9 KB -
MD5: 7de327971177c2124d8f388a19b1c4c6
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Mar 26, 2020
Rehbein, Ines; Ruppenhofer, Josef; Steen, Julius, 2020, "MACE-AL", https://doi.org/10.11588/data/C2OQN4, heiDATA, V1
A method for detecting noise in automatically annotated sequence-labelled data, combining MACE (Hovy et al. 2013) with Active Learning. |
Mar 26, 2020 -
MACE-AL
ZIP Archive - 326.8 KB -
MD5: 056a7e70a8f8b6e8fa72e3eead763d39
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