@inproceedings{RehbeinRuppenhofer2020,
  author    = {Ines Rehbein and Josef Ruppenhofer},
  title     = {A New Resource for German Causal Language},
  series = {Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC), May 11-16, 2020, Palais du Pharo, Marseille, France},
  editor    = {Nicoletta Calzolari and Fr{\´e}d{\´e}ric B{\´e}chet and Philippe Blache and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and H{\´e}l{\`e}ne Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association},
  address   = {Paris},
  isbn      = {979-10-95546-34-4},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-98692},
  pages     = {5968 -- 5977},
  year      = {2020},
  abstract  = {We present a new resource for German causal language, with annotations in context for verbs, nouns and adpositions. Our dataset includes 4,390 annotated instances for more than 150 different triggers. The annotation scheme distinguishes three different types of causal events (CONSEQUENCE, MOTIVATION, PURPOSE). We also provide annotations for semantic roles, i.e. of the cause and effect for the causal event as well as the actor and affected party, if present. In the paper, we present inter-annotator agreement scores for our dataset and discuss problems for annotating causal language. Finally, we present experiments where we frame causal annotation as a sequence labelling problem and report baseline results for the prediciton of causal arguments and for predicting different types of causation.},
  language  = {en}
}