@inproceedings{albogamy-etal-2017-arabic,
    title = "{A}rabic Tweets Treebanking and Parsing: A Bootstrapping Approach",
    author = "Albogamy, Fahad  and
      Ramsay, Allan  and
      Ahmed, Hanady",
    editor = "Habash, Nizar  and
      Diab, Mona  and
      Darwish, Kareem  and
      El-Hajj, Wassim  and
      Al-Khalifa, Hend  and
      Bouamor, Houda  and
      Tomeh, Nadi  and
      El-Haj, Mahmoud  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Third {A}rabic Natural Language Processing Workshop",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/W17-1312/",
    doi = "10.18653/v1/W17-1312",
    pages = "94--99",
    abstract = "In this paper, we propose using a {\textquotedblleft}bootstrapping{\textquotedblright} method for constructing a dependency treebank of Arabic tweets. This method uses a rule-based parser to create a small treebank of one thousand Arabic tweets and a data-driven parser to create a larger treebank by using the small treebank as a seed training set. We are able to create a dependency treebank from unlabelled tweets without any manual intervention. Experiments results show that this method can improve the speed of training the parser and the accuracy of the resulting parsers."
}