@inproceedings{papay-pado-2019-quotation,
    title = "Quotation Detection and Classification with a Corpus-Agnostic Model",
    author = "Papay, Sean  and
      Pad{\'o}, Sebastian",
    editor = "Mitkov, Ruslan  and
      Angelova, Galia",
    booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
    month = sep,
    year = "2019",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/fix-sig-urls/R19-1103/",
    doi = "10.26615/978-954-452-056-4_103",
    pages = "888--894",
    abstract = "The detection of quotations (i.e., reported speech, thought, and writing) has established itself as an NLP analysis task. However, state-of-the-art models have been developed on the basis of specific corpora and incorpo- rate a high degree of corpus-specific assumptions and knowledge, which leads to fragmentation. In the spirit of task-agnostic modeling, we present a corpus-agnostic neural model for quotation detection and evaluate it on three corpora that vary in language, text genre, and structural assumptions. The model (a) approaches the state-of-the-art on the corpora when using established feature sets and (b) shows reasonable performance even when us- ing solely word forms, which makes it applicable for non-standard (i.e., historical) corpora."
}