@InProceedings{liepins-EtAl:2017:EACLDemo,
  author    = {Liepins, Renars  and  Germann, Ulrich  and  Barzdins, Guntis  and  Birch, Alexandra  and  Renals, Steve  and  Weber, Susanne  and  van der Kreeft, Peggy  and  Bourlard, Herve  and  Prieto, Jo\~{a}o  and  Klejch, Ondrej  and  Bell, Peter  and  Lazaridis, Alexandros  and  Mendes, Alfonso  and  Riedel, Sebastian  and  Almeida, Mariana S. C.  and  Balage, Pedro  and  Cohen, Shay B.  and  Dwojak, Tomasz  and  Garner, Philip N.  and  Giefer, Andreas  and  Junczys-Dowmunt, Marcin  and  Imran, Hina  and  Nogueira, David  and  Ali, Ahmed  and  Miranda, Sebasti\~{a}o  and  Popescu-Belis, Andrei  and  Miculicich Werlen, Lesly  and  Papasarantopoulos, Nikos  and  Obamuyide, Abiola  and  Jones, Clive  and  Dalvi, Fahim  and  Vlachos, Andreas  and  Wang, Yang  and  Tong, Sibo  and  Sennrich, Rico  and  Pappas, Nikolaos  and  Narayan, Shashi  and  Damonte, Marco  and  Durrani, Nadir  and  Khurana, Sameer  and  Abdelali, Ahmed  and  Sajjad, Hassan  and  Vogel, Stephan  and  Sheppey, David  and  Hernon, Chris  and  Mitchell, Jeff},
  title     = {The SUMMA Platform Prototype},
  booktitle = {Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {116--119},
  abstract  = {We present the first prototype of the SUMMA Platform: an integrated platform
	for multilingual media monitoring. The platform contains a rich suite of
	low-level and high-level natural language processing technologies: automatic
	speech recognition of broadcast media, machine translation, automated tagging
	and classification of named entities, semantic parsing to detect relationships
	between entities, and automatic construction / augmentation of factual
	knowledge bases. Implemented on the Docker platform, it can easily be deployed,
	customised, and scaled to large volumes of incoming media streams.},
  url       = {http://aclweb.org/anthology/E17-3029}
}