Processing effort is a poor predictor of cross-linguistic word order frequency

Brennan Gonering, Emily Morgan


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.
Anthology ID:
2020.conll-1.18
Volume:
Proceedings of the 24th Conference on Computational Natural Language Learning
Month:
November
Year:
2020
Address:
Online
Editors:
Raquel Fernández, Tal Linzen
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
245–255
Language:
URL:
https://aclanthology.org/2020.conll-1.18
DOI:
10.18653/v1/2020.conll-1.18
Bibkey:
Cite (ACL):
Brennan Gonering and Emily Morgan. 2020. Processing effort is a poor predictor of cross-linguistic word order frequency. In Proceedings of the 24th Conference on Computational Natural Language Learning, pages 245–255, Online. Association for Computational Linguistics.
Cite (Informal):
Processing effort is a poor predictor of cross-linguistic word order frequency (Gonering & Morgan, CoNLL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.conll-1.18.pdf