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Empirical Linguistics and Computational Language Modeling (LiMo) (Department of Computational Linguistics of Heidelberg University and Leibniz Institute for the German Language)
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31 to 40 of 55 Results
Sep 2, 2019
Wiegand, Michael, 2019, "Lexicon of Abusive Words (EN)", https://doi.org/10.11588/data/MKPEYV, heiDATA, V1
This goldstandard contains a bootstrapped lexicon of abusive words. The lexicon comprises a large set of English negative polar expressions annotated as either abusive or not.
ZIP Archive - 738.4 KB - MD5: 46f33f5b7a9c866b1a2fb6dc956b945d
Markdown Text - 4.4 KB - MD5: 3cbbac5ff1534a6e9c3fcc9a1b0be976
Documentation
Sep 2, 2019
Wiegand, Michael, 2019, "Opinion role extractor", https://doi.org/10.11588/data/3W7AQP, heiDATA, V1
System for the Extraction of Subjective Expressions, Sentiment Sources and Sentiment Targets from German Text
Sep 2, 2019 - Opinion role extractor
ZIP Archive - 20.8 MB - MD5: 6704c06c5a8566eb05c3a8e0e0baebc2
Code
Sep 2, 2019 - Opinion role extractor
Plain Text - 13.0 KB - MD5: c4eb5b271a38da142c703216f9648f09
Documentation
Aug 23, 2019
van den Berg, Esther, 2019, "Twitter Titling Corpus", https://doi.org/10.11588/data/IOHXDF, heiDATA, V1, UNF:6:+F3lLKziwMvjy+xyktkilw== [fileUNF]
The Twitter Titling Corpus contains 4002 stance-annotated tweets collected between 20 June 2017 and 30 August 2017 mentioning 6 presidents. Each tweet is annotated for the naming form used to refer to the president, for the purpose of a study on the relation between naming variat...
Aug 23, 2019 - Twitter Titling Corpus
Tab-Delimited - 219.0 KB - MD5: 16948c910c278125330395cd182a5551
Data
Aug 19, 2019
Kotnis, Bhushan, 2019, "Negative Sampling for Learning Knowledge Graph Embeddings", https://doi.org/10.11588/data/YYULL2, heiDATA, V1
Reimplementation of four KG factorization methods and six negative sampling methods. Abstract Knowledge graphs are large, useful, but incomplete knowledge repositories. They encode knowledge through entities and relations which define each other through the connective structure o...
ZIP Archive - 19.4 KB - MD5: d2e8ac74e3f20d2cdec2225962c7e2f0
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