@InProceedings{abreu-oliveira:2018:S18-1,
  author    = {Abreu, Carla  and  Oliveira, Eugénio},
  title     = {FEUP at SemEval-2018 Task 5: An Experimental Study of a Question Answering System},
  booktitle = {Proceedings of The 12th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {667--673},
  abstract  = {We present the approach developed at the Faculty of Engineering of the University of Porto to participate in SemEval-2018 Task 5: Counting Events and Participants within Highly Ambiguous Data covering a very long tail.The work described here presents the experimental system developed to extract entities from news articles for the sake of Question Answering. We propose a supervised learning approach to enable the recognition of two different types of entities: Locations and Participants. We also discuss the use of distance-based algorithms (using Levenshtein distance and Q-grams) for the detection of documents' closeness based on the entities extracted. For the experiments, we also used a multi-agent system that improved the performance.},
  url       = {http://www.aclweb.org/anthology/S18-1109}
}