@inproceedings{hektoen-1997-probabilistic,
    title = "Probabilistic Parse Selection based on Semantic Cooccurrences",
    author = "Hektoen, Eirik",
    editor = "Nijholt, Anton  and
      Berwick, Robert C.  and
      Bunt, Harry C.  and
      Carpenter, Bob  and
      Hajicova, Eva  and
      Johnson, Mark  and
      Joshi, Aravind  and
      Kaplan, Ronald  and
      Kay, Martin  and
      Lang, Bernard  and
      Lavie, Alon  and
      Nagao, Makoto  and
      Steedman, Mark  and
      Tomita, Masaru  and
      Vijay-Shanker, K.  and
      Weir, David  and
      Wittenburg, Kent  and
      Wiren, Mats",
    booktitle = "Proceedings of the Fifth International Workshop on Parsing Technologies",
    month = sep # " 17-20",
    year = "1997",
    address = "Boston/Cambridge, Massachusetts, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/1997.iwpt-1.15/",
    pages = "113--122",
    abstract = "This paper presents a new technique for selecting the correct parse of ambiguous sentences based on a probabilistic analysis, of lexical cooccurrences in semantic forms. The method is called {\textquotedblleft}Semco{\textquotedblright} (for semantic cooccurrence analysis) and is specifically targeted at the differential distribution of such cooccurrences in correct and incorrect parses. It uses Bayesian Estimation for the cooccurrence probabilities to achieve higher accuracy for sparse data than the more common Maximum Likelihood Estimation would. It has been tested on the Wall Street Journal corpus (in the PENN Treebank) and shown to find the correct parse of 60.9{\%} of parseable sentences of 6-20 words."
}