@inproceedings{goodman-1997-probabilistic,
    title = "Probabilistic Feature Grammars",
    author = "Goodman, Joshua",
    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/add-emnlp-2024-awards/1997.iwpt-1.13/",
    pages = "89--100",
    abstract = "We present a new formalism, probabilistic feature grammar (PFG). PFGs combine most of the best properties of several other formalisms, including those of Collins, Magerman, and Charniak, and in experiments have comparable or better performance. PFGs generate features one at a time, probabilistically, conditioning the probabilities of each feature on other features in a local context. Because the conditioning is local, efficient polynomial time parsing algorithms exist for computing inside, outside, and Viterbi parses. PFGs can produce probabilities of strings, making them potentially useful for language modeling. Precision and recall results are comparable to the state of the art with words, and the best reported without words."
}