@inproceedings{ens-etal-2019-morphosyntactic,
    title = "Morphosyntactic Disambiguation in an Endangered Language Setting",
    author = {Ens, Jeff  and
      H{\"a}m{\"a}l{\"a}inen, Mika  and
      Rueter, Jack  and
      Pasquier, Philippe},
    editor = "Hartmann, Mareike  and
      Plank, Barbara",
    booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
    month = sep # "–" # oct,
    year = "2019",
    address = "Turku, Finland",
    publisher = {Link{\"o}ping University Electronic Press},
    url = "https://preview.aclanthology.org/ingest_wac_2008/W19-6139/",
    pages = "345--349",
    abstract = "Endangered Uralic languages present a high variety of inflectional forms in their morphology. This results in a high number of homonyms in inflections, which introduces a lot of morphological ambiguity in sentences. Previous research has employed constraint grammars to address this problem, however CGs are often unable to fully disambiguate a sentence, and their development is labour intensive. We present an LSTM based model for automatically ranking morphological readings of sentences based on their quality. This ranking can be used to evaluate the existing CG disambiguators or to directly morphologically disambiguate sentences. Our approach works on a morphological abstraction and it can be trained with a very small dataset."
}