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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)

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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Mar 26, 2020 - MACE-AL
ZIP Archive - 326.8 KB - MD5: 056a7e70a8f8b6e8fa72e3eead763d39
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Mar 26, 2020 - MACE-AL-TREE
ZIP Archive - 141.9 KB - MD5: 7de327971177c2124d8f388a19b1c4c6
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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
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.
Plain Text - 18.2 KB - MD5: 4a17ffc27c9f3b240fbf4fe17783c89c
Documentation
Plain Text - 18.2 KB - MD5: 4a17ffc27c9f3b240fbf4fe17783c89c
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ZIP Archive - 738.4 KB - MD5: 46f33f5b7a9c866b1a2fb6dc956b945d
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 - 19.4 KB - MD5: d2e8ac74e3f20d2cdec2225962c7e2f0
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