431 to 440 of 715 Results
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
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. |
Jul 26, 2016Propylaeum@heiDATA
Seit 1917 erscheint die von der Römisch-Germanischen Kommission herausgegebene Zeitschrift "Germania". Sie publiziert wissenschaftliche Aufsätze und Buchbesprechungen. Eingereichte Manuskripte (deutsch, englisch, französisch) unterliegen dem Peer-Review-Verfahren. Das "Germania D... |
Jan 20, 2021 - Empirical Linguistics and Computational Language Modeling (LiMo)
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... |
Aug 15, 2023 - NCT - Section of Translational Medical Ethics
Anger, Michael; Wendelborn, Christian; Schickhardt, Christoph, 2023, "German funders' data sharing policies - A qualitative interview study [interview excerpts]", https://doi.org/10.11588/data/FJAG0X, heiDATA, V1
Background Data sharing is commonly seen as beneficial for science, but is not yet common practice. Research funding agencies are known to play a key role in promoting data sharing, but German funders’ data sharing policies appear to lag behind in international comparison. This s... |
Mar 26, 2020 - Empirical Linguistics and Computational Language Modeling (LiMo)
Rehbein, Ines; Ruppenhofer, Josef, 2020, "German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)", https://doi.org/10.11588/data/ZHI94V, heiDATA, V1
Annotations of causal verbs, nouns and prepositions in context and lexicon file for causal verbs, nouns and prepositions. |
Dec 10, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Becker, Maria, 2019, "GER_SET: Situation Entity Type labelled corpus for German", https://doi.org/10.11588/data/BBQYD0, heiDATA, V1
Semantic clause types, also called Situation Entity (SE) types (Smith, 2003) are linguistic characterizations of aspectual properties shown to be useful for tasks like argumentation structure analysis (Becker et al., 2016), genre characterization (Palmer and Friedrich, 2014), and... |
Dec 17, 2015 - Universitätsbibliothek Heidelberg
Antretter, Marlene; Eller, Dirk; Elstermann, Hannes; Geissler, Stefan; Grüning, Simon; Horn, Sebastian; Kohler, Matthias; Kuck, Kevin; Lingnau, Anna; Nozik, Alexandra; Odenwald, Jakob; Rieger, Felix; Schubert, Christopher; Wenze, Felix; Zimmermann, Karin, 2015, "Georeferencing of the "Lorscher Codex"", https://doi.org/10.11588/data/10063, heiDATA, V1
Collection of historic place names from the Lorscher Codex (1176-1200). Most of the (deserted) villages and cities named in the codex had been in possession of Abbey Lorsch, many of them are mentioned for the first time here. In the project the property should be visualised in mo... |
Feb 23, 2021
Open research data from the research group "Geomorphology, Soil Geography and Geoarchaeology" at the Institute of Geography of Heidelberg University. |
Dec 7, 2023
Data publications of the Geo- and Cosmochemistry Research Group at the Institute of Earth Science of Heidelberg University. |
Oct 22, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Becker, Maria, 2019, "Genre-sensitive Neural Situation Entity classifier (DE, EN)", https://doi.org/10.11588/data/XXKWU0, heiDATA, V1
This is a Classifier for situation entity types as described in Becker et al., 2017. These clause types depend on a combination of syntactic-semantic and contextual features. We explore this task in a deeplearning framework, where tuned word representations capture lexical, synta... |