Empirical Linguistics and Computational Language Modeling (LiMo)

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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41 to 50 of 148 Results

causal_language_DE_release1.0.zip Mar 26, 2020 - German causal language annotations and lexicon (verbs, nouns, prepositions) (DE) ZIP Archive - 1.6 MB - MD5: f928beb9f56c4a3e011941904872a4eb Data
README.md Mar 26, 2020 - German causal language annotations and lexicon (verbs, nouns, prepositions) (DE) Markdown Text - 7.8 KB - MD5: 705940dda9344f994549436966482467 Documentation
MACE-AL.zip Mar 26, 2020 - MACE-AL ZIP Archive - 326.8 KB - MD5: 056a7e70a8f8b6e8fa72e3eead763d39 Code
MACE-AL-TREE.zip Mar 26, 2020 - MACE-AL-TREE ZIP Archive - 141.9 KB - MD5: 7de327971177c2124d8f388a19b1c4c6 Code
convert.zip Mar 26, 2020 - Converter for content-to-head style syntactic dependencies ZIP Archive - 10.1 MB - MD5: 30167cb475d743ced8aa63e6349a99ce CodeDocumentation
readme.txt Mar 26, 2020 - Converter for content-to-head style syntactic dependencies Plain Text - 1.2 KB - MD5: fc57366f049837b691c85a50b3e47b46 Documentation
social-media-POS-testsuite.conllu Mar 26, 2020 - A harmonised testsuite for social media POS tagging (DE) Unknown - 2.9 MB - MD5: 8bf35bfb77317b4d789fb0387454f118 Data
example.txt Mar 26, 2020 - Pre-trained POS tagging models for German social media Plain Text - 333 B - MD5: fef85f2d0d0a34d965014646659e5222
hunpos-social-media.model.bz2 Mar 26, 2020 - Pre-trained POS tagging models for German social media Bzip Archive - 6.0 MB - MD5: 130e09643a6ec5b26bcdf520571f261d Data
output.txt Mar 26, 2020 - Pre-trained POS tagging models for German social media Plain Text - 639 B - MD5: 1dc8fa318270ae3612341c0065889549

causal_language_DE_release1.0.zip

Mar 26, 2020 - German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)

ZIP Archive - 1.6 MB -

Data

README.md

Mar 26, 2020 - German causal language annotations and lexicon (verbs, nouns, prepositions) (DE)

Markdown Text - 7.8 KB -

Documentation

MACE-AL.zip

Mar 26, 2020 - MACE-AL

ZIP Archive - 326.8 KB -

Code

MACE-AL-TREE.zip

Mar 26, 2020 - MACE-AL-TREE

ZIP Archive - 141.9 KB -

Code

convert.zip

Mar 26, 2020 - Converter for content-to-head style syntactic dependencies

ZIP Archive - 10.1 MB -

CodeDocumentation

readme.txt

Mar 26, 2020 - Converter for content-to-head style syntactic dependencies

Plain Text - 1.2 KB -

Documentation

social-media-POS-testsuite.conllu

Mar 26, 2020 - A harmonised testsuite for social media POS tagging (DE)

Unknown - 2.9 MB -

Data

example.txt

Mar 26, 2020 - Pre-trained POS tagging models for German social media

Plain Text - 333 B -

hunpos-social-media.model.bz2

Mar 26, 2020 - Pre-trained POS tagging models for German social media

Bzip Archive - 6.0 MB -

Data

output.txt

Mar 26, 2020 - Pre-trained POS tagging models for German social media

Plain Text - 639 B -

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