@inproceedings{macavaney-etal-2018-gu,
    title = "{GU} {IRLAB} at {S}em{E}val-2018 Task 7: Tree-{LSTM}s for Scientific Relation Classification",
    author = "MacAvaney, Sean  and
      Soldaini, Luca  and
      Cohan, Arman  and
      Goharian, Nazli",
    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/iwcs-25-ingestion/S18-1133/",
    doi = "10.18653/v1/S18-1133",
    pages = "831--835",
    abstract = "SemEval 2018 Task 7 focuses on relation extraction and classification in scientific literature. In this work, we present our tree-based LSTM network for this shared task. Our approach placed 9th (of 28) for subtask 1.1 (relation classification), and 5th (of 20) for subtask 1.2 (relation classification with noisy entities). We also provide an ablation study of features included as input to the network."
}