@InProceedings{neves-EtAl:2017:BioNLP17,
  author    = {Neves, Mariana  and  Eckert, Fabian  and  Folkerts, Hendrik  and  Uflacker, Matthias},
  title     = {Assessing the performance of Olelo, a real-time biomedical question answering application},
  booktitle = {BioNLP 2017},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada,},
  publisher = {Association for Computational Linguistics},
  pages     = {342--350},
  abstract  = {Question answering (QA) can support physicians and biomedical researchers to
	find answers to their questions in the scientific literature. Such systems
	process large collections of documents in real time and include many natural
	language processing (NLP) procedures. We recently developed Olelo, a QA system
	for biomedicine which includes various NLP components,
	such as question processing, document and passage retrieval, answer processing
	and multi-document summarization. In this work, we present an evaluation of our
	system on the the fifth BioASQ challenge. We participated with the current
	state of the application and with an extension based on semantic role labeling
	that we are currently investigating. In addition
	to the BioASQ evaluation, we compared our system to other on-line biomedical QA
	systems in terms of the response time and the quality of the answers.},
  url       = {http://www.aclweb.org/anthology/W17-2344}
}