@inproceedings{santus-etal-2018-bomji,
    title = "{B}om{J}i at {S}em{E}val-2018 Task 10: Combining Vector-, Pattern- and Graph-based Information to Identify Discriminative Attributes",
    author = "Santus, Enrico  and
      Biemann, Chris  and
      Chersoni, Emmanuele",
    editor = "Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      May, Jonathan  and
      Shutova, Ekaterina  and
      Bethard, Steven  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/S18-1163/",
    doi = "10.18653/v1/S18-1163",
    pages = "990--994",
    abstract = "This paper describes BomJi, a supervised system for capturing discriminative attributes in word pairs (e.g. yellow as discriminative for banana over watermelon). The system relies on an XGB classifier trained on carefully engineered graph-, pattern- and word embedding-based features. It participated in the SemEval-2018 Task 10 on Capturing Discriminative Attributes, achieving an F1 score of 0.73 and ranking 2nd out of 26 participant systems."
}