@InProceedings{richter-EtAl:2017:EMNLP2017Demos,
  author    = {Richter, Ludwig  and  Gei{\ss}, Johanna  and  Spitz, Andreas  and  Gertz, Michael},
  title     = {HeidelPlace: An Extensible Framework for Geoparsing},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {85--90},
  abstract  = {Geographic information extraction from textual data sources, called geoparsing,
	is a key task in text processing and central to subsequent spatial analysis
	approaches. Several geoparsers are available that support this task, each with
	its own (often limited or specialized) gazetteer and its own approaches to
	toponym detection and resolution. In this demonstration paper, we present
	HeidelPlace, an extensible framework in support of geoparsing. Key features of
	HeidelPlace include a generic gazetteer model that supports the integration of
	place information from different knowledge bases, and a pipeline approach that
	enables an effective combination of diverse modules tailored to specific
	geoparsing tasks. This makes HeidelPlace a valuable tool for testing and
	evaluating different gazetteer sources and geoparsing methods. In the
	demonstration, we show how to set up a geoparsing workflow with HeidelPlace and
	how it can be used to compare and consolidate the output of different
	geoparsing approaches.},
  url       = {http://www.aclweb.org/anthology/D17-2015}
}