@InProceedings{rehbein-ruppenhofer:2017:LAW,
  author    = {Rehbein, Ines  and  Ruppenhofer, Josef},
  title     = {Catching the Common Cause: Extraction and Annotation of Causal Relations and their Participants},
  booktitle = {Proceedings of the 11th Linguistic Annotation Workshop},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {105--114},
  abstract  = {In this paper, we present a simple, yet effective method for the automatic
	identification and extraction of causal relations from text, based on a large
	English-German parallel corpus. The goal of this effort is to create a lexical
	resource for German causal relations. The resource will consist of a lexicon
	that describes constructions that trigger causality as well as the participants
	of the causal event, and will be augmented by a corpus with annotated instances
	for each entry, that can be used as training data to develop a system for
	automatic classification of causal relations. Focusing on verbs, our method
	harvested a set of 100 different lexical triggers of causality, including
	support verb constructions. At the moment, our corpus includes over 1,000
	annotated instances. The lexicon and the annotated data will be made available
	to the research community.},
  url       = {http://www.aclweb.org/anthology/W17-0813}
}