@inproceedings{aquino-de-leon-2020-parsing,
    title = "Parsing in the absence of related languages: Evaluating low-resource dependency parsers on {T}agalog",
    author = "Aquino, Angelina  and
      de Leon, Franz",
    editor = "de Marneffe, Marie-Catherine  and
      de Lhoneux, Miryam  and
      Nivre, Joakim  and
      Schuster, Sebastian",
    booktitle = "Proceedings of the Fourth Workshop on Universal Dependencies (UDW 2020)",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2020.udw-1.2/",
    pages = "8--15",
    abstract = "Cross-lingual and multilingual methods have been widely suggested as options for dependency parsing of low-resource languages; however, these typically require the use of annotated data in related high-resource languages. In this paper, we evaluate the performance of these methods versus monolingual parsing of Tagalog, an Austronesian language which shares little typological similarity with any existing high-resource languages. We show that a monolingual model developed on minimal target language data consistently outperforms all cross-lingual and multilingual models when no closely-related sources exist for a low-resource language."
}