@inproceedings{van-cranenburgh-2018-active,
    title = "Active {DOP}: A constituency treebank annotation tool with online learning",
    author = "van Cranenburgh, Andreas",
    editor = "Zhao, Dongyan",
    booktitle = "Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/C18-2009/",
    pages = "38--42",
    abstract = "We present a language-independent treebank annotation tool supporting rich annotations with discontinuous constituents and function tags. Candidate analyses are generated by an exemplar-based parsing model that immediately learns from each new annotated sentence during annotation. This makes it suitable for situations in which only a limited seed treebank is available, or a radically different domain is being annotated. The tool offers the possibility to experiment with and evaluate active learning methods to speed up annotation in a naturalistic setting, i.e., measuring actual annotation costs and tracking specific user interactions. The code is made available under the GNU GPL license at \url{https://github.com/andreasvc/activedop}."
}