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Dataset . 2022
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Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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LeiKo

Authors: Jablotschkin, Sarah; Zinsmeister, Heike;
Abstract

LeiKo is a comparable corpus of German easy-to-read news texts. This freely available resource is systematically compiled and linguistically annotated for linguistic and computational linguistic research. LeiKo consists of 216 news and newspaper texts (approx. 56,600 tokens) and their meta data structured in four subcorpora according to the websites they were published on. All texts are tokenized, lemmatized, part-of-speech tagged and dependency parsed and can be queried in ANNIS (Krause/Zeldes 2016). A core corpus of 40 texts is manually corrected. Version 0.9 contains only the core corpus with lemma and pos annotations and can be queried here: https://corpora.uni-hamburg.de/hzsk/de/hzsk_access/annis/leiko Version 1.0 comprises all 216 texts and not only lemma and pos annotations, but also syntactic annotations and metadata. The corpus is provided in the annis format, which can be directly imported into ANNIS Kickstarter. Version 1.1 is identical to version 1.0, but in addition to the annis files contains all corpus texts in the conll format. In version 1.3, some parts in the tazleicht subcorpus were added that were missing due to a mistake in the Python script written to gather the texts from the websites. In addition, the syntactic segmentation for lists was revised and the URL for each text was added to the set of meta data. Version 1.4 contains additional coreference annotations. Version 1.5 contains corrected meta data annotations as well as annotations of discourse relations according to the Penn Discourse Treebank guidelines (Webber et al. 2019) in separate csv files (currently not searchable in ANNIS). Further versions with additional manual annotation levels will follow. If you use the corpus, please cite: Jablotschkin, Sarah / Heike Zinsmeister (2020): ���LeiKo: A corpus of easy-to-read German���. Poster presentation at the Computational Linguistics Poster Session in the course of the 42nd annual conference of the Deutsche Gesellschaft f��r Sprachwissenschaft (DGfS) in Hamburg. (The version of the poster you find in the download section was corrected for typos.)

If you use the corpus, please cite: Jablotschkin, Sarah / Heike Zinsmeister (2020): "LeiKo: A corpus of easy-to-read German". Poster presentation at the Computational Linguistics Poster Session in the course of the 42nd annual conference of the Deutsche Gesellschaft f��r Sprachwissenschaft (DGfS) in Hamburg. (The version of the poster you find in the download section was corrected for typos.)

Related Organizations
Keywords

easy-to-read, Easy Language, Leichte Sprache, ANNIS, corpus linguistics, linguistics, Plain German, Corpus, conll, news texts, einfache Sprache, annotation, Easy German, Plain Language, text simplification, newspaper

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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