Topological Field Labeler for German (doi:10.11588/data/YYNQFF)

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Part 1: Document Description
Part 2: Study Description
Part 5: Other Study-Related Materials
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Document Description

Citation

Title:

Topological Field Labeler for German

Identification Number:

doi:10.11588/data/YYNQFF

Distributor:

heiDATA

Date of Distribution:

2023-11-13

Version:

1

Bibliographic Citation:

Do, Bich-Ngoc; Rehbein, Ines, 2023, "Topological Field Labeler for German", https://doi.org/10.11588/data/YYNQFF, heiDATA, V1

Study Description

Citation

Title:

Topological Field Labeler for German

Identification Number:

doi:10.11588/data/YYNQFF

Authoring Entity:

Do, Bich-Ngoc (Institute of Computational Linguistics, Heidelberg University & Leibniz Institute for German Language)

Rehbein, Ines (Leibniz Institute for German Language)

Date of Production:

2020

Distributor:

heiDATA

Access Authority:

Do, Bich-Ngoc

Holdings Information:

https://doi.org/10.11588/data/YYNQFF

Study Scope

Keywords:

Arts and Humanities, Computer and Information Science, syntactic parsing, topological field, sequence labeling

Topic Classification:

Dependency Parsing

Abstract:

<p>This resource contains the code of the topological labeler used in the paper: Do and Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". For this tool, labeling topological field is formulated as a sequence labeling task. We also include in this resource two pre-trained models on the TüBa-D/Z dataset with German SPMRL styled POS tags that are used in the paper.</p>

Kind of Data:

source code

Kind of Data:

pre-trained model

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Bich-Ngoc Do and Ines Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". In: <em>Proceedings of the 28th International Conference on Computational Linguistics</em>. Barcelona, Spain (Online): International Committee on Computational Linguistics, pp. 2049–2061.

Identification Number:

10.18653/v1/2020.coling-main.185

Bibliographic Citation:

Bich-Ngoc Do and Ines Rehbein (2020). "Parsers Know Best: German PP Attachment Revisited". In: <em>Proceedings of the 28th International Conference on Computational Linguistics</em>. Barcelona, Spain (Online): International Committee on Computational Linguistics, pp. 2049–2061.

Other Study-Related Materials

Label:

README.md

Notes:

text/markdown

Other Study-Related Materials

Label:

topological-field-labeler.zip

Notes:

application/zip

Other Study-Related Materials

Label:

README.md

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text/markdown

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Label:

split1024328679.tar.gz

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application/gzip

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Label:

split1024328679_marmot.tar.gz

Notes:

application/gzip

Other Study-Related Materials

Label:

baseline-marmot.tar.gz

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application/gzip

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baseline.tar.gz

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application/gzip

Other Study-Related Materials

Label:

README.md

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text/markdown

Other Study-Related Materials

Label:

embeddings.tar.gz

Notes:

application/gzip

Other Study-Related Materials

Label:

README.md

Notes:

text/markdown