@InProceedings{seganti-EtAl:2019:S19-2,
  author    = {Seganti, Alessandro  and  Sobol, Helena  and  Orlova, Iryna  and  Kim, Hannam  and  Staniszewski, Jakub  and  Krumholc, Tymoteusz  and  Koziel, Krystian},
  title     = {NLPR@SRPOL at SemEval-2019 Task 6 and Task 5: Linguistically enhanced deep learning offensive sentence classifier},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {712--721},
  abstract  = {The paper presents a system developed for the SemEval-2019 competition Task 5 hat- Eval Basile et al. (2019) (team name: LU Team) and Task 6 OffensEval Zampieri et al. (2019b) (team name: NLPR@SRPOL), where we achieved 2nd position in Subtask C. The system combines in an ensemble several models (LSTM, Transformer, OpenAI’s GPT, Random forest, SVM) with various embeddings (custom, ELMo, fastText, Universal Encoder) together with additional linguistic features (number of blacklisted words, special characters, etc.). The system works with a multi-tier blacklist and a large corpus of crawled data, annotated for general offensiveness. In the paper we do an extensive analysis of our results and show how the combination of features and embedding affect the performance of the models.},
  url       = {http://www.aclweb.org/anthology/S19-2126}
}