@inproceedings{gonering-morgan-2020-processing,
    title = "Processing effort is a poor predictor of cross-linguistic word order frequency",
    author = "Gonering, Brennan  and
      Morgan, Emily",
    editor = "Fern{\'a}ndez, Raquel  and
      Linzen, Tal",
    booktitle = "Proceedings of the 24th Conference on Computational Natural Language Learning",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.conll-1.18/",
    doi = "10.18653/v1/2020.conll-1.18",
    pages = "245--255",
    abstract = "Some have argued that word orders which are more difficult to process should be rarer cross-linguistically. Our current study fails to replicate the results of Maurits, Navarro, and Perfors (2010), who used an entropy-based Uniform Information Density (UID) measure to moderately predict the Greenbergian typology of transitive word orders. We additionally report an inability of three measures of processing difficulty {---} entropy-based UID, surprisal-based UID, and pointwise mutual information {---} to correctly predict the correct typological distribution, using transitive constructions from 20 languages in the Universal Dependencies project (version 2.5). However, our conclusions are limited by data sparsity."
}