Data publications of the Leibniz ScienceCampus “Empirical Linguistics and Computational Language Modeling”

The Leibniz ScienceCampus “Empirical Linguistics and Computational Language Modeling” (LiMo) is a cooperative research project between the Leibniz Institute for the German Language (Leibniz-Institut für Deutsche Sprache, IDS) in Mannheim and the Department of Computational Linguistics at Heidelberg University (ICL). The general aims of the project are to develop new methods, models, and tools for compiling and analysing automatically large German textual corpora covering different domains, genres and language varieties.

The project is supported by funds from the Baden-Württemberg Ministry of Science, Research and the Arts and the Leibniz Association together with funds provided by the Leibniz Institute for the German Language and Heidelberg University.

Funding Period: 2015 – 2020

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21 to 30 of 185 Results
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
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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
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Sep 2, 2019
Wiegand, Michael, 2019, "GermEval-2018 Corpus (DE)", https://doi.org/10.11588/data/0B5VML, heiDATA, V1
This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection.
ZIP Archive - 14.8 MB - MD5: 6471a35acf802906383e6d19e5241b37
Code
Markdown Text - 2.1 KB - MD5: 82583130d72db06eb5fe686c1a8338ac
Documentation
Sep 5, 2019
Wiegand, Michael; Ruppenhofer, Josef; Schulder, Marc, 2019, "Sentiment View Lexicon (EN)", https://doi.org/10.11588/data/2JK48O, heiDATA, V1
This gold standard contains sentiment expressions (verbs, nouns and adjectives) that have been annotated according to their (prior) sentiment view. Each sentiment expression is labelled either as actor or speaker view.
Plain Text - 18.2 KB - MD5: 4a17ffc27c9f3b240fbf4fe17783c89c
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