@inproceedings{do-rehbein-2017-evaluating,
    title = "Evaluating {LSTM} models for grammatical function labelling",
    author = "Do, Bich-Ngoc  and
      Rehbein, Ines",
    editor = "Miyao, Yusuke  and
      Sagae, Kenji",
    booktitle = "Proceedings of the 15th International Conference on Parsing Technologies",
    month = sep,
    year = "2017",
    address = "Pisa, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W17-6318/",
    pages = "128--133",
    abstract = "To improve grammatical function labelling for German, we augment the labelling component of a neural dependency parser with a decision history. We present different ways to encode the history, using different LSTM architectures, and show that our models yield significant improvements, resulting in a LAS for German that is close to the best result from the SPMRL 2014 shared task (without the reranker)."
}