MobIE: A German Dataset for Named Entity Recognition, Entity Linking and Relation Extraction in the Mobility Domain

Leonhard Hennig, Phuc Tran Truong, Aleksandra Gabryszak

In: Proceedings of KONVENS-2021. Konferenz zur Verarbeitung natürlicher Sprache (KONVENS-2021) September 6-9 Düsseldorf/Hybrid Germany ACL 2021.


We present MobIE, a German-language dataset, which is human-annotated with 20 coarse- and fine-grained entity types and entity linking information for geographically linkable entities.The dataset consists of 3,232 social media texts and traffic reports with 91K tokens, and contains 20.5K annotated entities, 13.1k of which are linked to a knowledge base. A subset of the dataset is human-annotated with seven mobility-related, n-ary relation types, while the remaining documents are annotated using a weakly-supervised labeling approach implemented with the Snorkel framework. To the best of our knowledge, this is the first German-language dataset that combines annotations for NER, EL and RE, and thus can be used for joint and multi-task learning of these fundamental information extraction tasks. We make MobIE public at


Konvens_2021_MobIE_Corpus_camera_ready.pdf (pdf, 829 KB )

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz