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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11 to 20 of 148 Results

en-ptb-forest64.tar.gz Nov 13, 2023 - Datasets for Dependency Tree Reranking Gzip Archive - 35.0 MB - MD5: 6d218b2ea37fe551338634e6d77aeb05 Data
README.md Nov 13, 2023 - Datasets for Dependency Tree Reranking Markdown Text - 1.2 KB - MD5: 647a783e60a80234a80ffbf5869a314b Documentation
README.md Nov 13, 2023 - Datasets for Dependency Tree Reranking Markdown Text - 1.0 KB - MD5: e04a0cc53e6f6bc041a32d02befdc889 Documentation
bilstm-parser.zip Nov 13, 2023 - Head Selection Parsers and LSTM Labelers ZIP Archive - 58.8 KB - MD5: 1994899f6e96118e147ea9565193198b Code
README.md Nov 13, 2023 - Head Selection Parsers and LSTM Labelers Markdown Text - 1.8 KB - MD5: aa0872f2f4fb632dd0a09b2faccb9927 Documentation
README.md Nov 13, 2023 - Head Selection Parsers and LSTM Labelers Markdown Text - 470 B - MD5: 0c88b76a2a9e9d2de5c2f0ceeb605fa9 Documentation
README.md Nov 13, 2023 - Head Selection Parsers and LSTM Labelers Markdown Text - 3.0 KB - MD5: 7cb511b7bf6510aa7c1f9f7ba47a98d8 Documentation
spmrl-char-pos.tar.gz Nov 13, 2023 - Head Selection Parsers and LSTM Labelers Gzip Archive - 19.7 MB - MD5: fa08751359eab07a3b4bda8a0d6efb70 Data
spmrl-comp-pos.tar.gz Nov 13, 2023 - Head Selection Parsers and LSTM Labelers Gzip Archive - 22.9 MB - MD5: b65835b64f1ffd3fc28b2b5397a3dbd8 Data
spmrl-head-pos.tar.gz Nov 13, 2023 - Head Selection Parsers and LSTM Labelers Gzip Archive - 31.0 MB - MD5: 7c5e35e942bf91effcad7a1e94673d1d Data

en-ptb-forest64.tar.gz

Nov 13, 2023 - Datasets for Dependency Tree Reranking

Gzip Archive - 35.0 MB -

Data

README.md

Nov 13, 2023 - Datasets for Dependency Tree Reranking

Markdown Text - 1.2 KB -

Documentation

README.md

Nov 13, 2023 - Datasets for Dependency Tree Reranking

Markdown Text - 1.0 KB -

Documentation

bilstm-parser.zip

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

ZIP Archive - 58.8 KB -

Code

README.md

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

Markdown Text - 1.8 KB -

Documentation

README.md

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

Markdown Text - 470 B -

Documentation

README.md

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

Markdown Text - 3.0 KB -

Documentation

spmrl-char-pos.tar.gz

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

Gzip Archive - 19.7 MB -

Data

spmrl-comp-pos.tar.gz

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

Gzip Archive - 22.9 MB -

Data

spmrl-head-pos.tar.gz

Nov 13, 2023 - Head Selection Parsers and LSTM Labelers

Gzip Archive - 31.0 MB -

Data

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