@inproceedings{halacsy-etal-2006-using,
    title = "Using a morphological analyzer in high precision {POS} tagging of {H}ungarian",
    author = "Hal{\'a}csy, P{\'e}ter  and
      Kornai, Andr{\'a}s  and
      Oravecz, Csaba  and
      Tr{\'o}n, Viktor  and
      Varga, D{\'a}niel",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Gangemi, Aldo  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Odijk, Jan  and
      Tapias, Daniel",
    booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
    month = may,
    year = "2006",
    address = "Genoa, Italy",
    publisher = "European Language Resources Association (ELRA)",
    url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/488_pdf.pdf",
    abstract = "The paper presents an evaluation of maxent POS disambiguation systems that incorporate an open source morphological analyzer to constrain the probabilistic models. The experiments show that the best proposed architecture, which is the first application of the maximum entropy framework in a Hungarian NLP task, outperforms comparable state of the art tagging methods and is able to handle out of vocabulary items robustly, allowing for efficient analysis of large (web-based) corpora.",
}