GeNeG: German News Knowledge Graph

Item Type:	Dataset
Title:	GeNeG: German News Knowledge Graph
Date:	2022
Creator:	Iana, Andrea ORCID: 0000-0002-7248-7503 ; Grote, Alexander ; Ludwig, Katharina ORCID: 0000-0001-9815-7222 ; Alam, Mehwish ; Müller, Philipp ORCID: 0000-0002-5351-0608 ; Weinhardt, Christof ; Sack, Harald ; Paulheim, Heiko ORCID: 0000-0003-4386-8195
Divisions:	School of Business Informatics and Mathematics > Data Science (Paulheim 2018-)

DDC Classification:	004 Computer science, internet
Abstract:	GeNeG is a knowledge graph constructed from news articles on the topic of refugees and migration, collected from German online media outlets. GeNeG contains rich textual and metadata information, as well as named entities extracted from the articles' content and metadata and linked to Wikidata. The graph is expanded with up to three-hop neighbors from Wikidata of the initial set of linked entities. GeNeG comes in three flavors: Base GeNeG: contains textual information, metadata, and linked entities extracted from the articles. Entities GeNeG: derived from the Base GeNeG by removing all literal nodes, it contains only resources and it is enriched with three-hop Wikidata neighbors of the entities extracted from the articles. Complete GeNeG: the combination of the Base and Entities GeNeG, it contains both literals and resources. (English)
External Identifier for Data:	https://doi.org/10.5281/zenodo.6039372

URL:	https://madata.bib.uni-mannheim.de/927/
Access (Controlled):	Only Metadata
License (Controlled):	No license information available, not specified, or non-standard license

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Date Deposited:	08 May 2026 14:04
Last Modified:	08 May 2026 14:04