@inproceedings{faruqui10:_training,
  abstract = {We present a freely available optimized Named Entity Recognizer (NER) for German. It alleviates the small size of available NER training corpora for German with distributional generalization features trained on large unlabelled corpora. We vary the size and source of the generalization corpus and find improvements of 6\% F1-score (in-domain) and 9\% (out-of-domain) over simple supervised training.},
  added-at = {2017-04-03T19:28:28.000+0200},
  address = {Saarbr\"ucken, Germany},
  author = {Faruqui, Manaal and Pad{\'o}, Sebastian},
  biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2dcd9b65c809ef88a1c294d60243100a2/sp},
  booktitle = {Proceedings of KONVENS 2010},
  interhash = {16475c614f540914d7300f477009d829},
  intrahash = {dcd9b65c809ef88a1c294d60243100a2},
  keywords = {conference myown},
  timestamp = {2017-04-03T17:28:32.000+0200},
  title = {Training and Evaluating a {G}erman Named Entity
                  Recognizer with Semantic Generalization},
  url = {http://www.nlpado.de/~sebastian/pub/papers/konvens10_faruqui.pdf},
  year = 2010
}