CLOct 1, 2015

Response to Liu, Xu, and Liang (2015) and Ferrer-i-Cancho and Gómez-Rodríguez (2015) on Dependency Length Minimization

arXiv:1510.00436v1
Originality Synthesis-oriented
AI Analysis

This work clarifies and defends empirical findings on a linguistic universal, which is incremental in refining evidence for dependency length minimization.

The authors address criticisms of their prior work on dependency length minimization across languages, acknowledging an error in failing to cite previous research but arguing that their study provides novel, strong evidence for this as a universal property by using baselines that control for alternative theories.

We address recent criticisms (Liu et al., 2015; Ferrer-i-Cancho and Gómez-Rodríguez, 2015) of our work on empirical evidence of dependency length minimization across languages (Futrell et al., 2015). First, we acknowledge error in failing to acknowledge Liu (2008)'s previous work on corpora of 20 languages with similar aims. A correction will appear in PNAS. Nevertheless, we argue that our work provides novel, strong evidence for dependency length minimization as a universal quantitative property of languages, beyond this previous work, because it provides baselines which focus on word order preferences. Second, we argue that our choices of baselines were appropriate because they control for alternative theories.

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